ETHNICITY, INSURGENCY, AND CIVIL WAR∗
James D. Fearon and David D. Laitin
Department of Political Science
Stanford University
Stanford, CA 94305-2044
3/30/00
Abstract
An influential conventional wisdom holds that civil wars proliferated rapidly with
the end of the Cold War and that the root cause of many or most of these has been
ethnic nationalism. We show that the current prevalence of internal war is mainly the
result of a steady accumulation of protracted conflicts since the 50s and 60s rather than
a sudden change associated with a new, post-Cold War international system. We also
find that after controlling for per capita incomes and growth rates, more ethnically or
religiously diverse countries have been no more likely to experience significant civil war
in this period. We argue for understanding civil war in this period in terms of insurgency
or rural guerrilla warfare, a particular form of military practice that can be harnessed to
diverse political agendas, including but not limited to ethnic nationalism. The factors
that explain which countries have been at risk for civil war are not their ethnic or religious
characteristics but rather the conditions that favor insurgency. These include poverty
and slow growth, which favor rebel recruitment and mark financially and bureaucratically
weak states, rough terrain, and large populations.
∗ To be presented at the first LiCEP Meetings, Duke University, April 21-23, 2000. This is a first draft;
comments are greatly appreciated. The authors gratefully acknowledge the support of the National Science
Foundation (grants SES-9876477 and SES-9876530), and also the Center for Advanced Study in the Behavioral
Sciences, supported by funds from the William and Flora Hewlett Foundation.
1
Introduction
Civil war, and especially civil war involving ethnic groups fighting to control
or secede from a state, is a if not the central dilemma of international security
affairs since the collapse of the Soviet Union in 1991. The end of the Cold
War has helped to unleash powerful, long-standing forces of ethnic nationalism
that have produced a host of bloody civil wars in Eastern Europe, the former
Soviet Union, and subSaharan Africa. The root cause of these civil wars is the
nationalism of culturally distinct ethnic minorities who rebel either because they
harbor grievances arising from discrimination by ethnic majorities, or because
ethnic or “civilizational” cleavages within a state are simply untenable.
These judgments represent a highly influential conventional wisdom. One
finds it expressed almost daily by journalists and state leaders, and quite often
by political scientists as well. We shall argue that it is largely inconsistent with
the empirical evidence on civil war since decolonization. In the first place, the
prevalence of civil wars in the 1990s is the result of a gradual, longer term trend
rather than a sudden change in the international system. Second, we find that
countries with significant ethnic or religious minorities are no more or less likely
to have civil wars, once we control for economic factors. Nor does ethnic or
religious difference significantly influence the magnitude of civil wars. Third,
among states at similar levels of economic development and with similar growth
rates, neither democracies nor federations are less likely to experience ethnic or
other civil wars, as one might expect if civil wars were driven primarily by the
ethnic grievances.
The main factors influencing which countries and groups will see civil war
in this period are not cultural differences and ethnic grievances, but rather the
conditions that favor insurgency. Insurgency is a technology of military conflict characterized by small, lightly armed bands practicing guerrilla warfare
from rural base areas. As a form of warfare, insurgency can be and has been
harnessed to diverse political agendas. Indeed, the concept is most closely associated with the communist insurgencies fought in Latin America, Asia, and
Africa during the Cold War. Ethnic antagonisms and nationalist sentiments
may help an insurgent group at the margin, but other factors are much more
important. In brief, we argue that insurgency is favored by (1) poverty and slow
economic growth, which aid the recruitment of fighters; (2) a rural base area
(preferably with rough, inaccesible terrain), and local knowledge of the population superior to the government’s, which allows rebels to hide from superior
1
government forces; and (3) a financially, organizationally, and politically weak
central government, which facilitates the operation of an insurgent band.
Empirically, we show that per capita income in 1960, growth of per capita
from 1960 to 1980, country population in 1960, French colonial status, and
relatively mountainous terrain are together powerful predictors of whether a
country has a civil war after 1980. We argue that per capita income and growth
rates proxy for both ease of recruitment and the central government’s ability to
maintain effective rural policing or to prosecute an effective counterinsurgency.
Former French colonies, especially in subSaharan Africa, have been less likely
to have civil wars due to an explicit French policy of intervening on behalf
of postcolonial states to help crush rebellions. Large rural populations, we
argue, are harder for relatively impoverished central governments to monitor,
and are also empirically associated with countries that have more diverse and
wild terrain.
We do not argue that nationalism and ethnic grievances are irrelevant.
These are, after all, the political agendas that insurgencies increasingly profess. We do not contest the reality of cultural differences, nationalist sentiment,
state discrimination and abuse along ethnic and religious lines, and rebel groups
whose leaders are at least in part motivated by such concerns. We argue simply that the presence of such factors does not appear to distinguish between
countries with more and less civil violence. In addition, if our argument about
insurgency is correct, then the conventional wisdom may be too quick to attribute the motivation for ethnic civil wars to a uniform sense of group grievance
or antagonism, rather than to the grievances and ambitions of insurgent bands
with the knowledge and tools to induce local support of their agendas.
In the next section we present some basic descriptive statistics on civil
violence since 1945. We then briefly review the conventional nationalist or ethnic
interpretation before developing the insurgency perspective, first informally and
then with a model to resolve questions about the logic of the argument. Section
6 presents the data and its analysis. A brief conclusion follows.
2
Civil war since the 1950s
Using data from three different civil war lists, Figure 1 shows the number of
countries with ongoing civil wars by year since World War II. Covering slightly
2
different time intervals, the sources are the Correlates of War (COW) data on
civil and “extra-systemic” wars (1945-92), the State Failure (SF) Project data
on (what the project called) ethnic and revolutionary wars (1954-96), and data
from the International Institute for Strategic Studies (IISS), which essentially
updates the list in Sivard (1996) through 1999.1 The COW and SF projects
give similar definitions for civil war, requiring a minimum total killed (1000 for
COW, 100 per year for SF) in a contest between a government and a nonstate
actor or actors that is not completely one-sided (a massacre or genocide).2 No
explicit definition is given for the Sivard/IISS data, although it appears that a
minimum of 1000 estimated killed was applied, and, as the figure suggests, the
congruence with the other sources is very high (particularly with the SF data).3
The common trend in Figure 1 suggests that contrary to popular belief,
the prevalence of civil wars is not a post-Cold War phenomenon.4 There is
indeed a jump up in 1991 and 1992 associated with the collapse of the Soviet
Union (and a few other cases), but this is followed by a significant decline in
the next few years of the 1990s. Even with this decline, the percentage of all
countries with ongoing civil wars remains high, at 20% in 1995, down from a
high of 28% in 1991.5
Rather than suddenly appearing with the end of the Cold War, these data
from several sources suggest that the prevalence of civil wars in the 1990s is due
1 The State Failure project data and codebook are available from the website
http://www.bsos.umd.edu/cidcm/stfail/. The IISS data is contained the in map included
with IISS (2000).
COW claims to require that each side incur at least 5% (check) of total fatalities, while SF
requires that “each party must mobilize 1000 or more people (armed agents, demonstrators,
troops) and an average of 100 or more fatalities per year must occur during the episode.” For
more on the definitions, see COW xxx and the SF codebook, pages x-x.
2
3 Note that the SF data considers only independent countries, so colonial wars are excluded.
This accounts for the slightly lower starting point for the SF line in the 1950s. In adapting
the data for this figure and for subsequent analysis, we assign colonial wars like Algeria or
Mau Mau to the colonial power in the Sivard/IISS data, since, ex ante, these were civil wars
just as much as the war today in Chechnya is.
The general pattern observed in these three sources appears in others as well; for example,
Lickliders’ (1995) list, and the research reported by Gantzell (1997). In the last case, Gantzell
provides a figure that looks remarkably similar to Figure 1 here.
4
Using the SF data and all countries that had over 500,000 in 1990 population according
to the World Bank for the denominators.
5
3
to a steady, essentially linear accumulation of conflicts since the 1950s. Using
the SF data on the number of conflicts, civil wars have broken out at a rate of
about 2.44 per year in this period, and they have ended at a rate of about 1.84
per year.6 There is no statistically discernible trend in the annual difference
between number of civil wars breaking out and the number that end.7 The
prevalence of violent civil conflicts in the 1990s – more than a quarter of all
states had at least one on-going at the higher water mark of 1991 – is the result
of a gradual, longer term trend rather than a sudden change in the international
system.8 Indeed, these data indicate that if the end of the Cold War is associated
with any trend at all it would be a reduction in the amount of civil war, though
it is perhaps too soon to say.
The evidence summarized in Figure 1 suggests three striking puzzles:
1. Why have some countries had civil wars in this period while most others
have not?
2. Relatedly, why have some ethnic, religious, and other communal groups
been involved in significant fighting against state forces while most others
have not?
3. Why are these conflicts so persistent and difficult to end? Why has the
rate of outbreak exceeded the rate at which they are settled or otherwise
concluded?
3
The nationalism script
The conventional wisdom noted in the introduction suggests answers to all three
questions. Briefly put, what we will call the nationalism script proposes that:
Note that this is not quite the same as the number of countries with conflicts, since some
countries have had multiple concurrent wars.
6
Regressing this difference on years produces a coefficient that cannot be statistically distinguished from zero.
7
One might wonder if the gradual increase is accounted for by the increase in the number
of countries in the international system over this period. But if we presented the variable
on the y-axis in Figure 1 as ongoing wars per total independent countries in the system, the
pattern looks almost identical.
8
4
1. Countries with culturally distinct ethnic or religious minorities are more
likely to have civil wars. At least in the modern period, nationalist movements are likely in such states either because of state and majority group
oppression along the lines of cultural difference, or simply due to the yearning of ethnic minorities for self-government. In turn, both oppression and
demands for self-government often yield civil war.
2. Ethnic and religious minorities are more likely to see significant fighting
with the state, the more culturally distinct they are from the majority
group or groups, and (relatedly, in these arguments) the more they suffer
discrimination and oppression.
3. Such civil wars are especially difficult to end because they are about matters
of cultural or national identity, over which compromises and bargains are
difficult and often impossible.
A range of theories of ethnic nationalism tend to agree on these implications. Using a broad brush, we can distinguish between perennialist and modernist (or constructivist) positions on the nature and sources of ethnic nationalism. perennialist arguments, given in purest form by nationalist politicians and
journalists reporting on nationalist conflicts in progress, stress long-standing
(“ancient”) cultural practices said to define and distinguish ethnic groups. Differences between these practices are argued to make conflict nearly inevitable.9
By contrast, modernist theories see the thorough-going politicization of
cultural difference that ethnic nationalism represents as a development of the
last 200 to 500 years.10 The core argument is that economic modernization and
the development of the modern state make upward social mobility possible, but
contingent on sharing the culture of the group that dominates state or society.
When state or society pose cultural barriers to upward mobility for minority
groups, the minorities will develop nationalist movements and violence becomes
more likely. All the more so, according Deutsch (1953), Gellner (1983), and
9 Academics rarely make such arguments as baldly as do nationalist leaders. But authors
who stress the long-standing, “deep” nature of ethnic differences and suggest that these make
domestic peace difficult include Horowitz (1985), Smith (1986), Hastings (1997), Moynihan
(1993), Ignatieff (1993), and Huntington (1996). Arguably, the main message of Horowitz’s
influential book on ethnic conflict is that ethnically plural societies face a host of pathologies
that render them especially prone to conflict and, at the extreme, violence.
Depending on which modernist you consult – see Deutsch (1953), Gellner (1983), Anderson
(1983), Hobsbawm (1992), Greenfeld (1992).
10
5
Anderson (1983), the greater the preexisting cultural differences between the
minority group and the dominant group. (When the preexisting differences are
slight, assimilation is more likely.)
So the two approaches yield the same predictions about the relationship
between cultural diversity and civil conflict.
The cases of civil war in the sources for Figure 1 might seem to provide
prima facie support for the nationalism script. A large number are indeed
“ethnic wars” as the term is commonly understood. It is impossible to draw a
sharp line between ethnic and nonethnic (or “ideological”) civil wars. For any
definition close to ordinary language notions, there are ambiguous cases, such
as the wars in Guatemala, Sierra Leone, or Mozambique. Nonetheless, we can
begin to get a rough sense of the prevalence of “ethnic” civil wars by asking
how many of these conflicts involve rebel organizations that seek secession or
greater regional autonomy on behalf of a people who are claimed to be ethnically
or religiously distinct. By our own rough codings, about 44 of the 106 (42%)
conflicts listed in the SF data have been “secessionist” in this broad sense. This
undercounts “ethnic civil wars” as the term is usually understood, since it omits
cases where ethnically based coalitions have fought for control of the state, as in
Afghanistan, Rwanda, Somalia, Lebanon, or more ambiguously, Sierra Leone.
Our rough count of such cases yields 27, bringing the total to 71 of 106 or about
two thirds of all cases in this data set.11
But the prevalence of “ethnic” war in this period does not imply that ethnically and religiously diverse countries are more prone to civil war than others.
To assess this we need to compare countries with more and less ethnic and religious diversity. Before proceeding to the empirics, we develop an alternative
interpretation of violent civil conflicts in this period.
4
Insurgency
If many post-1945 civil wars have been “ethnic” or “national” as these terms are
usually understood, then even more have been fought as insurgencies. Insurgency is a technology of military conflict characterized by small, lightly armed
11
[SF codings yield 59-64 or so ethnic, 50 revolutionary. Look into this.]
6
bands practicing guerrilla warfare from rural base areas.12 By our rough coding,
about 76 of the 107 violent conflicts listed in the State Failure data involved
insurgency in this sense, and almost all of the “ethnic” wars were insurgencies.13
We shall argue that to explain why some countries and groups have experienced civil and ethnic civil wars in this period, one needs to understand
the conditions that favor insurgency, which are to a large extent independent
of cultural differences between groups and even group grievances. These conditions are best summarized by way of a somewhat fuller though still compressed
statement of the logic of insurgency.14
The fundamental fact about insurgency is that insurgents are weak relative
to the governments they are fighting, at least at the start of operations. We
mean “weak” in a specific sense here. Call it absolute weakness: If government
forces knew who the rebels were and how to find them, they would be fairly
easily destroyed or captured. This is typically true even in states whose military
and police capacities are low. (Contrast this to relations between states, where
each knows where to find the other and more-or-less what to expect, but usually
lacks the desire or ability to crush the other.)
The absolute weakness of the insurgents has several implications. First
and most important, it means that to survive the rebels must be able to hide
from government forces. Thus, some conditions that favor insurgency are: (1)
rough terrain, poorly served by roads, at a distance from the centers of state
power; (2) foreign, cross-border sanctuaries; and (3) a local population that can
be induced not to denounce the insurgents to government agents.
The nationalism script and a good deal of scholarly writing on civil wars
holds that ethnic solidarity and grievances are necessary for (3), the local population’s support of active rebels. In line with some analysts of communist insurgencies (e.g. Leites and Wolf (1970), Thompson (1966), Clutterbuck (1967),
Kalyvas (1999)), we argue that while grievances and ethnic differences can be
helpful in this regard, they are by no means necessary. Instead, the key to inducing the local population not to denounce the active rebels is local knowledge, or
The literature on guerrilla warfare is very large; see, for important examples, Griffith
(1961), Desai and Eckstein (1990), Laqueur (1976).
12
13
coding, differences, the rest ...
Though our formulations often differ, we have been greatly influenced here by Stathis
Kalyvas’ work on the Greek civil war.
14
7
private information about who is doing what at the village level. Local knowledge allows the active rebels to credibly threaten retribution for denunciation
and other acts that hurt them.15 Much evidence indicates that ethnic insurgents use this informational advantage to great effect, often threatening and
inflicting unimaginably harsh sanctions on “their own” people (Kalyvas 1999).
The nationalist script is mistaken, therefore, to infer from the presence of an
ethnic insurgency that the members of the ethnic group are of one mind in their
determination to fight the state till they realize a nationalist dream. Instead,
the attitudes of the nonrebel members of the ethnic minority are likely to reflect
a more complex mix of sentiments – anger at discrimination and (often) police
and army oppression by the dominant groups, but fear and unvoiced anger at
their self-appointed national champions.
An empirical implication of the importance of local knowledge is that
(3a) having a rural base greatly favors insurgency. In the city, anonymous
denunciation is generally easier to get away with, giving the government an
advantage in its counterinsurgent efforts.16
A second set of implications pertains to what might be called relative
weakness. Within the basic constraints of absolute weakness – the need to hide
and not be denounced by locals – insurgencies can be more or less able to wage
war against government (and other) targets. To survive, rebels need a supply
of arms and materiel, money to buy them, or smugglable goods to trade for
them. Relatedly, they need a supply of recruits to the insurgent way of life,
and they may also need know-how, information and instruction in the practical
details of running an insurgency. Perhaps most of all, they will be better able
to survive and prosper if the government they oppose is relatively weak: badly
financed, organizationally inept, corrupt, and poorly informed about goings on
at the local level. Effective counterinsurgency is extremely difficult even for wellequipped and well paid “modern” militaries; witness the U.S. military’s failures
A ‘second order’ mechanism by which ethnicity may favor insurgency is that ethnic minorities are sometimes marked by dense social networks that are isolated from dominant group
networks, thus giving an informational advantage to local rebels (Fearon and Laitin 1996).
But such an advantage does not require ethnic difference.
15
Northern Ireland is practically the only urban-based insurgency in the data. In a way,
it is an exception that proves the rule, given the efforts the paramilitaries have invested in
policing and punishing informants, and the efforts the British forces have made to cultivate
informants. Indeed, this is where the battle has been joined for most of the conflict since the
mid 70s. (need to research this more)
16
8
in Vietnam and the early British efforts in Northern Ireland. It goes beyond
problematic for less well-financed and bureaucratically competent states, which
either cannot prevent the abuse of local powers by field commanders, or may
even permit these abuses as a sort of tax farming to the military.
These observations yield the following conditions that favor insurgency:
(4) foreign governments or diasporas willing and able to supply weapons, money,
or training and know-how (this might be called “insurgency as international and
transnational politics by other means”); (5) land that supports the production
of high value, low weight goods such as coca, opium, diamonds, and to a lesser
degree timber and oil; (6) low income per capita and low growth in per capita
income, which make recruiting easier and will also be correlated with a resource
poor, often inept central government; (7) a large country population, which
makes it more difficult for the center to keep close tabs on who is doing what
at the local level, and also increases the number of potential recruits to an
insurgency for a given level of per capita income; (8) political instability at
the center, which would typically be an indicator of disorganization and weakness. Note that none of these conditions crucially involves cultural differences
or grievances.
5
Some theoretical puzzles
Factors that increase the military advantages of insurgents relative to the government will tend to increase civil violence. As is often the case, this superficially
plausible informal claim merits a closer look. At least three counterarguments
need to be addressed.
1. Why shouldn’t making rebels relatively stronger lead to a reduction in
government counterinsurgent effort, and thus perhaps a reduction in total
violence? After all, if counterinsurgency yields fewer returns for the same
costs, then shouldn’t the government do less of it?
2. Alternatively, what if making rebels relatively stronger simply leads to
an increase in counterinsurgency that completely offsets the increase in
rebellion?
3. Finally, why shouldn’t rebels with relative military advantages simply get
a better bargained settlement from the government, with no effect on the
9
amount of fighting necessary to reach it? More broadly, given that longrunning insurgencies create enormous destruction, what prevents bargained
settlements that avoid these costs?17
Although the focus of the paper is empirical, we pause to sketch a model
of insurgency that helps to answer these questions.18
5.1
A model of insurgency
In the course of a rebellion, the government adjusts its counterinsurgent effort
to the number and dangers posed by the rebels, while the scale of the rebellion
is in turn influenced by the governments’ effort. We propose a “reduced form”
model intended to capture the results of this process of mutual adjustment.
The actors in the model are a government and n individuals who could be
taken to represent a minority group or the entire country population, depending
on the application. Each individual i chooses between becoming an insurgent
and taking his or her best economic alternative, which yields utility yi ≥ 0.
Assume that the yi ’s are distributed according to a cumulative distribution
function F , which we can think of as the distribution of income in the society
or group.19 If the individual chooses to become an active rebel, he receives an
expected utility b(1 − p(c)) − p(c)d. p(c) is the probability of being captured
or killed by government forces when the government is spending c ≥ 0 on
counterinsurgency or policing. We assume that the probability of being captured
or killed increases with c at a constant or decreasing rate (p0 > 0, p00 ≤ 0). d > 0
is the (expected) cost of being killed or captured.
The expected benefits term b is intended to summarize all the immediate
attractions and disadvantages of life as a rebel. These may include the material benefits of theft, looting, or the successful appropriation of taxing powers
17 A common response is that a few individuals manage to benefit from an ongoing rebellion
that hurts many. But this begs the question, since we want to know what prevents using the
savings from ending a war to compensate or buy off these individuals.
18
See Fearon and Laitin (1999) for a fuller analysis of a very similar model.
19 The y ’s are chosen by Nature according to F at the start of the game. The government
i
knows F . Until we allow for transfers and bargaining, it is immaterial whether the government
also knows each individual’s yi .
10
in region; any status value or self-gratification from acting aggressively for a
nationalist cause; and material support from ethnic brethren. Not included in
this simple “one-round” game are benefits resulting from government transfers
or policy concessions such as regional autonomy. These should be modelled as
endogenous to the interaction, as we discuss below.
So, for a given level of counterinsurgency c, the individuals who want to
join the insurgency are those with the worst prospects in the modern or normal
economy20 – formally, all those with yi < ŷ ≡ b(1−p(c))−p(c)d. In equilibrium,
the number of rebels will be nF (ŷ).21
How, then, should the government choose its level of counterinsurgent or
policing effort, c? It is natural to suppose that the government cares about
the political and material damage caused by the rebels, and also the costs of
counterinsurgency. For simplicity, suppose that each surviving or uncaptured
rebel costs the government β > 0 times the cost of spending another unit
(say, a dollar) on counterinsurgency. Then the government’s total losses are
βm(1 − p(c)) + c, where m is the number of rebels and m(1 − p(c)) is the
number of rebels still active after the government’s counterinsurgent effort.
In an equilibrium, the government minimizes its total losses given the
number of rebels, while the number of rebels is in turn determined by the
government’s choice of c. The game so described has a unique Nash equilibrium
in which the government spends at a level c∗ and individuals with economic
prospects yi worse than a threshold level ŷ join the insurgency.22
This implication of the model is accurate – see Keen (1998) for some examples – but
too stark. In Latin America in particular, insurgencies have often been led by university
graduates (Wickham-Crowley 1992). A more realistic assumption would be that individuals
also vary in the benefits they derive from being a rebel. Some are more nationalistic than
others, some better at or more attracted by violence, and so on. If we make b i a random
variable uncorrelated with yi , then the model implies that rebellions should be staffed mainly
by those with the worst economic prospects, but not entirely.
20
21
For convenience we allow the number of rebels m to be fractional.
See the appendix. To be definite about the structure of play, assume that government and
individual choices are simultaneous. However, the results and even the details of the analysis
are equivalent if we have the individuals decide on whether to become rebels first, followed
by the government’s choice of c. Allowing the government to commit to c as a “Stackleberg
leader” prior to the rebellion choices yields the same results as in the Proposition below,
although the exact solutions will now involve characteristics of the density function of F .
22
11
The question of interest is how factors that make insurgents strong or
weak relative to the government influence the equilibrium level of violence. To
address this we introduce a parameter α that indexes all factors influencing the
rebels’ relative strength. Variables such as rough terrain, an inept or corrupt
military, poor local information available to the government, or foreign support
for the rebels reduce the government’s ability to capture and kill rebels for a
given level of counterinsurgent effort. Suppose, then, that the probability of
capture, p(c, α), depends on both c and α, and this probability falls as the
parameter α increases, holding counterinsurgency constant (p2 (c, α) < 0). By
contrast, α close to zero represents a powerfully advantaged government. To
capture this idea formally, we assume that (1) as the government gets very
strong relative to insurgents, any positive amount of counterinsurgent spending
produces a probability of capture approaching one; (2) as the government gets
very strong in relative terms, the marginal impact of spending something rather
than nothing increases without bound; and (3) as the insurgents get very strong
relative to the government, the marginal impact of the government spending
something rather than nothing approaches zero.23
These assumptions suffice for the following general results.
Proposition: (a) As the government becomes highly advantaged relative to the
rebels (α → 0), both the scale of the counterinsurgent effort c∗ and the scale of
the rebellion (nF (ŷ)) approach zero. (b) There exists a ᾱ > 0 such that for all
α > ᾱ, the government spends nothing on counterinsurgency (c∗ = 0) and the
number of rebels in equilibrium reaches its maximum possible value of nF (b).
A specific example is useful to illustrate the dynamics described in the
proposition. If yi is uniformly distributed between zero and Y and the probability of capturing or killing a rebel is p(c, α) = c/α for c ≤ α, then the
equilibrium number of rebels is m∗ = α/β and the government spends
b
Y
c =α
−α
b+d
nβ(b + d)
∗
!
for α < nbβ/Y . For α ≥ nbβ/Y , the government essentially “gives up,” spending c∗ = 0, while the number of rebels is m∗ = bn/Y .
Figure 2 illustrates these relationships. Note that in moving away from a
Formally, we have (1) limα→0 p(c, α) = 1∀c > 0; (2) limα→0 p1 (0, α) = ∞; and (3)
limα→∞ p1 (0, α) = 0. The choice of α = 0 to represent situations where counterinsurgency is
extremely effective is without loss of generality.
23
12
situation where the government is strongly advantaged, both rebellion and the
government’s counterinsurgent or police effort increase. Contrary to the suggestion in query 1 above, conferring military advantages on the rebels increases the
government response. The intuition: When the government is strongly advantaged by terrain, military competence, etc., it can spend very little and deter
all but a few from the hard life of insurgency. As the rebels gain advantages
(e.g., access to arms or training), the value of being a rebel for a given level
of counterinsurgent spending increases, causing an influx of new recruits. Even
though the government’s counterinsurgent spending is now less effective per
rebel, there are now more rebels, which means that the value of limiting damage by increased spending has increased. So the government initially increases
its counterinsurgent spending to rebels. (This observation answers question 1
above.) But precisely because counterinsurgent spending is now less effective per
rebel, the government prefers not to increase counterinsurgency enough to completely offset the increase in the scale of the rebellion (this addresses question 2).
Eventually, as rebel advantages grow greater, the number of rebels approaches
an upper bound, and additional counterinsurgent spending becomes ineffective
in any event. At some point, the government is better off scaling back its effort to save on counterinsurgency costs, because counterinsurgency has become
ineffective at limiting rebel depredations.
Total violence is a function of both the scale of the rebellion and the
scale of counterinsurgency. One plausible measure would be the number of
government kills and captures plus the number of uncaptured rebels (who are
assumed to engage in attacks to gain their rebel payoff b). This would imply
that total violence is proportional to p(c∗ , α)m∗ + (1 − p(c∗ , α))m∗ = m∗ . In this
case, then, the proposition implies that total violence increases as the rebels
gain military advantages relative to the government.
This completes our brief analysis of the dynamics of civil violence and
relative military advantage between government and rebels. Two additional results (proved in the appendix) will be used in the empirical analysis. First, both
the number of rebels and the government’s counterinsurgent effort increase with
the size of the country (or minority) population n. Larger populations produce
more rebels for a given level of counterinsurgent effort, although the per capita
amount of rebellion and government effort actually decrease with country size.
Larger populations produce more rebels for a given level of counterinsurgency,
which raises equilibrium levels of counterinsurgency, in turn lowering the per
13
capita number of rebels.24 Second, shifting the distribution of income downwards increases the equilibrium number of rebels and the government’s effort.
The informal arguments in section 4 also referred to the absolute weakness
of the rebels, the fact that if they could be identified and located by the government they would be readily crushed. Without presenting a full development,
it is worth indicating how a richer version of the model might analyze absolute
weakness.
Note first that the insurgency model could be redescribed as a model of
ordinary crime. Just relabel the actions of the citizens as “commit crime” or
not, and think of c as government expenditures on policing. This flexibility
is intentional. We believe there are important structural similarities in the
strategic problems in the two cases. But there are important differences as well,
pertaining in part to absolute weakness.
Ordinary criminals work solo or in small, ad hoc groups. They depend
on anonymity to avoid denunciation to the police. They attempt to burgle unseen or to mug isolated victims they will never encounter again. The central
strategic difference between ordinary criminals, on the one hand, and mafias
and insurgencies, on the other, is that the latter have the numbers and internal organization to threaten their victims/clients/“supporters” with retaliation
for denunciation. This allows them to engage in repeated transactions – typically, extracting/extorting taxes in various forms – from the same individuals.25
Mafias differ from insurgencies mainly in their political aims and, relatedly, their
attitude and incentives regarding the local population. Insurgent leaders aspire
to take over a state or to found a new one (or a regional autonomy).
To explore the implications of absolute weakness, we would need to model
explicitly the process by which counterinsurgency tries to extract information
about the identity and location of active rebels, and the process by which the
The model is not capturing one of the effects hypothesized in section 4, namely the argument that government information about local goings on will tend to be worse with larger
populations. This requires a model of absolute weakness; see below. Also, the specific example just given does not satisfy p11 < 0, which is why in that case m∗ does not vary with n or
F.
24
On the downside, however, internal organization implies that the capture of a single member may lead to the destruction of the whole outfit. Hence “cell structures,” the horrible
penalties for disloyalty found in both mafias and insurgencies, and government strategies of
witness protection in both cases.
25
14
rebel organization protects itself from denunciation. For instance, after individuals decide whether to become rebels, we could have the government in the
model randomly draw individuals from the population, who then receive a benefit for denouncing any rebel they know but pay a cost of retaliation with a
probability that depends on the number of rebels. This will create a “tipping
dynamic.” Where the rebels are expected to be strong the government will get
poor information, which makes counterinsurgency relatively ineffective and thus
favors a strong rebel force; where rebels are expected to be weak the government gets better information, and rebellion is less likely to get going (cf. Kalyvas
(1999)).
5.2
Obstacles to a bargained settlements
Why shouldn’t relative military advantages accruing to rebels simply gain them
a better negotiated settlement, without affecting the amount of fighting needed
to reach it? More generally, what prevents government and rebels from striking
a bargain that would save the government the costs of rebellion and counterinsurgency while saving rebels the risk of death and imprisonment?
The issues raised by these questions are complex; here we suggest only
that it is more promising to approach them from the view point of insurgency
than from nationalism. The difficulty of ending civil wars in the post-World War
II period may result not so much from the nature of the issues and combatants
– the assumption of internally homogenous ethnic groups contesting indivisible
stakes – as from the strategic implications of insurgent weakness.
To reduce the level of violence and spending on counterinsurgency, the
government can seek victory, or it can offer concessions in the form of policy
changes or more direct transfers (for instance, setting rebels up as leaders of
an autonomous region). The existence of an equilibrium with low or even quite
serious levels of civil violence in the model above reflects a reality, the prevalence of long-running, stalemated civil wars. Why don’t governments offer more
significant concessions to end these? Thinking in terms of the model sketched
above, there are significant obstacles to such a deal.
Suppose that prior to the choice of the counterinsurgency level c and the
individuals’ decisions whether to join a rebellion, the government can offer a
transfer in the form of policy concessions or something more focused. In the
first place, any transfers the government offers must be revokable or obtainable
15
only if one does not act as a rebel. Otherwise, the rebels can “pocket” the
concessions and continue fighting to gain the expected benefits b(1−p(c))−p(c)d.
Investments in regional infrastructure, the creation of local political institutions,
or even official acquiesence to political autonomy (a speech act), may be difficult
or impossible for the government to “take back.”
Second, to actually eliminate rebellion, any transfers or policy concessions
that the government makes must either be (a) focused on the potential or actual
rebels, (b) so great as to make even the most disgruntled (low yi ) rebels prefer
them to the rebel life, or (c) endow some subset of cooptable rebels with the
power and authority to police their own extremists.
Transfers or policy concessions that are not focused – such as regional
economic subsidies, a grant of regional autonomy or even secession – are inefficient for the government, in the sense that benefits are conferred on many
to influence a small number of active rebels. If the government in the model
above could commit to offer a policy benefit worth t to all individuals conditional on rebellion staying below some threshold level, this would only change
the behavior of individuals who would previously have been rebels but now have
yi + t > b(1 − p(c)) − p(c)d. With such generalized transfers it may make sense
for the government to “buy down” the level of rebellion somewhat as an alternative to counterinsurgency, but it will not in general be optimal to purchase
zero rebellion in this way – the extremists are too expensive.
Unfortunately, focused transfers, such as setting up rebels as regional leaders, run into problems with the implications of the insurgents’ absolute weakness. Absolute weakness implies that the bargaining power of the rebels depends on their being invisible to the government, hard to identify and locate.
But cutting a public deal that benefits them more than others may undermine
their invisibility and thus, ex post, their bargaining power. What prevents the
government from reneging? If, in the model, accepting a transfer gives the government the opportunity to kill or imprison rebels and the government cannot
commit itself against this, focused transfers will not work to end an insurgency.
In the Chittagong Hills of Bangladesh in 1980, a group of leaders showed up
to negotiate with the government representatives, only to be slaughtered by
security forces! (Society 1984) Cutting a credible deal with the government requires the rebels to have sufficient strength and reserves to be able to threaten
retaliation and renewed war for reneging by the government.26 Below this level
26
Cf. Walter (1997), who argues similarly that governments’ inability to commit prevents
16
of strength, costly low level war may be the best both sides can do. Above this
level of strength, the government faces dangers in endowing a rebel group with
official powers and control of government in its region, since these changes may
increase the ex post bargaining power of the rebels.
Finally, supposing that the above obstacles can be overcome, the rebels
need to be able to commit to comply with any deal in order for the government
to be willing to agree to it. Unless the government’s concessions lead all members of the group to prefer nonrebellion, then the rebels will need to be both
unified and have an internal structure for in-group policing. The necessity of
in-group policing is clear. Without it, concessions don’t buy the government
peace. But similarly, if there are multiple rebel groups and the government
cannot distinguish the source of attacks, members of one group have an incentive to blame peace-breaking attacks on the other group(s).27 In general, when
environmental and social conditions favor insurgency, rebel groups are prone to
splintering since unreconciled factions can easily hive off to continue fighting
after an agreement is reached. The anticipation of this inclines governments
towards fighting rather than bargaining, especially when the insurgents and the
groups they “represent” are highly divided internally. This is another condition
favoring insurgency (9).28
6
Empirical analysis
If the nationalist script is right, then countries with greater ethnic or religious
diversity should be more prone to civil war. In addition, following this standard
argument one might expect measures of democracy and federal organization
to be associated with civil peace, since these should be associated with lower
grievances, whether ethnic or not.
By contrast, we have argued that relatively small numbers of individuals
can make a significant insurgency if the conditions are right, so that measures
civil war settlements involving the disarmament of the rebels. But why not a settlement that
allows the rebels to keep their guns but stop using them? Our argument addresses this next
question as well.
Hence the use of IRA code words in the highly developed case of urban insurgency in
Northern Ireland.
27
28
cite NYT article on Mandela and Burundi negotiations, 1/17/00.
17
of cultural diversity and mechanisms for alleviating grievances will matter less
than the conditions that favor insurgency as a form of warfare. We suggested a
number of such conditions, though below we test only those for which we can
obtain data.
In brief, we expect higher per capita income and higher growth rates of
income to have two effects, both favoring civil peace. First, these should be
associated with state resources and state competence, and thus with more effective policing and counterinsurgency. Second, these should make the life of
a rebel less attractive compared to nonrebel alternatives. Mountainous terrain
should be associated with more rebellion and civil violence. Larger populations
should make counterinsurgency more difficult by putting the central government
at farther remove from the rural villages. Finally, we note that until the early
1990s, French governments pursued a policy of intervening to shore up and defend the leaders of their former colonies against internal revolts and rebellions,
especially in subSaharan Africa. This counts as a factor that makes the government strong relative to insurgents (other things equal), so we expect it to be
related to civil peace.
Tables 1-3 present a variety of regressions that help to evaluate these various conjectures. In every case the sample consists of the subset of the 159
countries with population greater than 500,000 in 1990 (using World Bank figures) for which we have data on the several regressors. The dependent variables
are either the log of two different measures of total deaths from civil war from
1980 to 1999 (State Failure Project and IISS/Sivard), or a dichotomous indicator of whether a country had a civil war after 1979 according to these two
sources. The dependent and independent variables are discussed next. Table
4 lists the variables used in the regressions. We discuss additional variables in
the text (indicated by italics).
Overall, the results are inconsistent with the main implications of the
nationalist script. The bivariate correlation between ethnic fractionalization
in a country and the log of total civil war deaths is indeed positive at .22.
However, as model 6 in Table 2 suggests, among countries with similar per
capita incomes and similar income growth rates, greater ethnolinguistic diversity
is not associated with greater amounts of killing or higher probabilities of civil
war. For religious diversity, even the bivariate relationship is essentially zero,
while it heads towards a negative relationship with civil violence, if anything,
after we control for other factors. One measure of democracy used in Table
2, based on the Polity III data, approaches statistical significance at the .10
18
level in the direction predicted by the nationalism script. As we discuss, below,
however, this is quite sensitive both to specification of the statistical model and
evaporates completely when we use the more theoretically appropriate measure
of democracy developed by Alvarez, Cheibub, Limongi and Przeworski (1996).
Finally, measures of federal organization of a state are completely unrelated to
levels of civil war, as we discuss below.
We discuss the variables and their estimated effects, issues of specification,
and additional controls next.
6.1
Dependent variables: measures of civil war
We use both a qualitative indicator – civil war, yes or no? – and the log of
a measure of total deaths in a country between 1980 and 1999 as dependent
variables.29
As far as we know, the only sources for total deaths in civil war that cover
this whole period are produced by the Institute for International and Strategic
Studies (hereafter IISS) (IISS 2000), whose list extends through 1999, and the
list originally compiled by William Eckhardt, given in Sivard (1996), which goes
to 1995.30 In fact, these are not fully separate sources, since IISS uses the Eckhardt data with very few changes or adjustments for conflicts that began and
ended before 1995. These data suffer serious liabilities. First, as noted above,
we cannot find any clear definition of the criteria for inclusion in these lists. The
implicit rule seems to be that the conflict must be estimated to have killed at
least a thousand people as a part of a contest for political power including an organized, rebel group or a government attacking an opposition publicly mobilized
29 Deaths are in thousands, with one added to avoid log of 0. We log deaths because the
distribution is highly skewed; otherwise a small number of extreme cases exert a very large
influence. Even after taking the log, the dependent variable looks not at all Normal (60% of
the countries are at zero), which raises concerns about bias in OLS. An alternative approach
is to use Tobit, viewing the countries with no civil war as left-censored observations of an
underlying, unobserved, Normally distributed variable. Since the results do not change under
Tobit, we present OLS and logit for ease of interpreting effect magnitudes. We also tried
estimated the distribution of standard errors through bootstrapping, and obtained virtually
identical results.
These sources estimate total deaths for a whole (or ongoing) conflict. For conflicts that
were ongoing in 1980 we simply divided the deaths estimates evenly over the years of conflict
listed.
30
19
to demand political change.31 The absence of a stated criterion for inclusion is
less problematic than it may initially appear, however, since the Eckardt and
IISS lists coincide to a high degree with other civil violence lists, such as the
Correlates of War data, Licklider (1995), the State Failure Project data, and,
for the 1990s, the Uppsala PRIO data on “armed conflicts” (Wallenstein and
Sollenberg 1997)
The second problem is that for most of the cases, the estimates of numbers
killed are clearly rough guesses. To a great extent this is inevitable for any such
enterprise. Counting the dead from civil violence would be extremely difficult
even if not for the powerful political incentives to inflate or deflate the numbers
and prevent investigations after the fact. We use these data because they appear
to be the best currently available with broad temporal and spatial coverage. We
believe that at a minimum they are serviceable as measures of relative orders
of magnitude across cases.
As a check, we have adapted the State Failure Project data, which includes
a five-point index of fatalities by year for roughly 107 civil conflicts between 1954
and 1996. Table 1 also includes estimates with this alternative measure. The
individual effect estimates are astonishingly similar, and the overall fit of the
models is generally better.32
An alternative response to the problem of estimating total deaths is to
give up, and instead estimate determinants of the probability that a country has
significant violence from civil conflict in a given period. Tables 1 and 3 also
report logistic regressions where the dependent variable takes a value of 1 for
countries that had some civil violence after 1979 reported in the IISS and SF
Eckhardt’s list sometimes also includes estimates of deaths from famine due to civil war,
as well as some cases of government massacres. The estimated famine deaths are excluded
from the IISS data, along with many though not all of the government massacres.
31
32 The levels of the five-point State Failure scale are: less than 100 fatalities, 100 to 1,000,
1,000 to 5,000, 5,000 to 10,000, and “more than 10,000” (codebook, pp. 7-8). For a measure
of total fatalities we took the log of one plus the sum of scores for each country for the years
1980 to 1996 for both “ethnic” and “revolutionary” wars. For cases where the SF coders
described a single war as both ethnic and revolutionary, we avoided double counting the
fatality estimates where possible. This measure is correlated with the IISS measure at .86.
To render the effect estimates in models 3 and 4 comparable to those in models 1 and 2,
we computed the IISS and SF measures for the period 1954 to 1996, and then regressed the
former on the latter to obtain coefficients to rescale the SF measure as a measure of log of
total deaths.
20
data sets. The results are again strikingly similar. A problem with this approach
is that the threshold of violence qualifying a country as having a “civil war”
or “significant civil violence” is somewhat arbitrary. (Certainly the ordinary
language notion of a proper civil war is larger than some of the 1000-to-5000killed cases included in this data. So we tried coding “wars” as beginning above
the thresholds of 5,000 and 10,000 dead based on the IISS data, with no change
in results.
6.2
Factors related and unrelated to civil violence
1. A country’s annual growth rate of per capita income from 1960 to 1979 is
negatively associated with both the occurrence and magnitude of post-79 civil
violence. Increasing a country’s annual growth rate by 1% per year for this period reduces its odds of a post-79 civil war by 34% and reduces estimated deaths
from civil violence by about 30% (using the estimates in model 1). Countries
in the 10th percentile on growth rate (at -2.35% per year) had on average five
times more post-79 deaths from civil war than did countries at the 90th percentile (2.71% per year).
Moreover, in contrast to the effect of per capita income (discussed below),
growth rates play a significant role in differentiating high and low violence cases
within geographic and cultural regions. Higher growth rates are negatively
related with post-79 civil war deaths in every region, and powerfully so in the
three regions with the most civil violence.33
Since civil violence can surely reduce economic growth, we have to worry
about confusing this effect with the impact of low growth rates on civil war.
This is why we measure growth rates (as well as per capita income) prior to
the period in which civil war is measured. The problem remains, however,
that if countries with civil wars in the period 1960 to 1979 are more likely to
have civil war after 1979, and civil violence causes lower growth rates, then the
estimated coefficient on growth rate may be biased upwards. There are at least
The bivariate correlations are -.44 for Asia, -.64 for North Africa/Middle East, and -.45 for
Subsaharan Africa. Income data is from the World Bank/Penn World Tables, supplemented
with estimates for the former Soviet republics in 1960 and 1980 based on the relative republican income estimates from McAuley (1979) and Penn World Tables (for 1990) respectively.
For the former Yugoslav republics we used Ramet (1992) estimates of relative incomes in 1962
and 1978, multiplied by the PWT estimates for Yugoslavia in 1960 and 1980.
33
21
two strategies for addressing this problem, neither perfect. The first, taken in
Tables 1 and 2, is to use only that part of the annual growth rate from 1960 to
1979 that is not “explained” by the log of war deaths from 1960 to 1979. That
is, the variable referred to in these regressions is not actually the annual growth
rate, but rather is the residuals from the regression of the annual growth rate
on log of deaths from civil violence between 1960 to 1979. This conservative
strategy credits any impact of the variation shared by 1960-79 growth and pre1980 deaths entirely to the latter. (If we use the actual growth rate variable in
model 1, the coefficient on growth rate increases in absolute value by 16%.)
An alternative, more problematic approach is to include 1960-to-1979
deaths as a control (see Table 3). Doing so, however, produces biased estimates, since the effects of any omitted variables are now wrongly assigned to
the pre-1980 deaths variable, biasing its coefficient estimate upwards. And since
pre-1980 deaths are without doubt significantly correlated with the other explanatory variables, their effect estimates are biased in unpredictable directions
as well (though most likely towards zero). This is what we observe in Table
3, although surprisingly the biggest impact is not on the effect estimate for
growth rates but on the estimates for income and country population. Even
so, it is reassuring that with the exception of the population variable with the
IISS measure of deaths, the same variables remain significant and the same
insignificant.34
2. Countries with higher per capita income in 1960 had significantly fewer
deaths from civil war after 1979 (and after 1960, for that matter). Doubling a
country’s 1960 per capita income is estimated to reduce the odds of a post-1979
civil war by a factor of more than three (other things equal), and to decrease
the expected number of deaths from civil war by about 40%. Moving from the
10th income percentile in 1960 ($537) to the 50th ($1586) reduces expected
civil war deaths after 1979 by a factor of 2.3. Moving from the 10th to the
90th ($5610) reduces expected post-7 deaths by a factor of almost six (using
coefficient estimates for model 1).
As noted, this effect arises mainly from comparisons of countries across
regions. Except within Asia and perhaps Latin America, knowing which counPerhaps civil war at time 1 actually causes more civil war at time 2 in a country, since
participants shift resources and acquire war-specific skills. If so (note that war-weariness
arguments cut the other way), we risk some omitted variable bias by excluding this cause.
But we can see no way to cleanly distinguish a causal effect of prior civil war from the effect
of unknown omitted variables.
34
22
tries were the richest in a region in 1960 would not have been a good guide for
predicting post-1979 civil war.35 Even so, income in 1960 does not appear just
to proxy for other characteristics of “Western” countries, since a dummy for
countries in this region is not significant when added to model 1.
3. Both total deaths from civil war and the probability of civil war have
been significantly greater for countries with greater total population in 1965 (or
any year, for that matter). If country A had twice the population of country
B in 1965, its odds of a post-79 civil war were twice as large and it had about
20% more civil war deaths, other things equal. Moving from the 10th percentile
(645,000) to the 90th (43 million) almost triples estimated post-1979 civil war
deaths. Note that deaths do not increase more than proportionally with population, so that per capita civil war deaths actually fall with country size. This
is the pattern predicted by the game model in section 5.
Total population is positively correlated with measures of cultural diversity, so that one might worry that the effect estimated here is in fact explained
by the nationalism script. But the estimate hardly changes when we control for
measures of ethnolinguistic and religious diversity (model 6).36
In part, the effect attributed to population may be due to rough terrain.
If we drop the population variable and substitute a dummy for countries where
the difference between the highest and lowest elevations is less than 1000 meters,
we find that these have about two-fifths as many post-79 civil war deaths on
average (p < .01). Model 5 shows the results when both are included; the
estimated effect on population drops a bit (especially with the SF measure of
deaths), and the estimate for flat countries is now a bit less precise.37
4. Former French colonies saw significantly less civil violence after 1979
and in fact for the whole post-colonial period. The estimated effect stems entirely from the French colonies in subSaharan Africa, where only 6 of the 17
Knowing per capita income in 1980 is a good predictor of post-79 war deaths, even within
regions, but this is largely due to the impact of economic growth rates in the interim. Growth
remains strongly significant with little change in the estimated coefficient if we use 1980
income rather than 1960, which suggests that it is the growth rate rather than just income
level that matters.
35
36
bias from 1000 death threshold?
In our present work we are seeking better measures of rough terrain, using digital elevation
maps drawn from satellite imaging.
37
23
former French colonies make the IISS civil war list (35%), compared to 16 of
the remaining 27 (60%). In addition, several of these are at present experiencing quite minor insurgencies (Tuaregs in Mali, Diolas in Senegal, and Afars
in Djibouti). The median number (estimated) killed in the French subSaharan
cases with civil violence is 1,500, compared to 102,000 for the non-French cases.
Outside of subSaharan Africa, the remaining ten former French colonies have
been if anything somewhat more likely to experience significant civil war (6 of
the 10, including Cambodia, Lebanon, and Algeria).
This pattern argues against an explanation in terms of implications of the
French legal system, the impact of French culture, or perhaps even the French
style of direct rather than indirect rule, since these imply that the effect should
hold across regions. It is more consistent with the hypothesis we advanced
above, that the well-known French policy of intervening to prop up the leaders
in their former African colonies made their governments relatively strong. In
effect, the colonial pax never ended – or has only recently ended – for the former
French colonies.38
5. Since conventional geographic regions put together countries perceived
to share many cultural, political, historical and economic features, a natural way
to check for omitted variables in a cross-national analysis is to ask if knowing a
country’s region allows one to improve one’s predictions. When regional dummy
variables are added singly to model 1 or 5, the only countries for which it helps
to know their region are those in North Africa and the Middle East.39 These
countries have had, on average, more than four times greater odds of having
an IISS or SF civil war, and more than four times as many deaths for civil war
than other countries as well.
We have no compelling explanation. Huntington (1996) has argued that
“Islam has bloody borders” because Islamic societies have cultural and demographic features that make them violence-prone. However, when we use a variJacques Foccart, the secretary to the French Presidency on Community and African Affairs, was legendary for his neo-colonial protection of French-favored regimes (Péan 1990).
Chad is an interesting exception, which has led Nolutshungu (1996) to a search for Foccart’s
nefarious purposes.
38
39 In some specifications, the dummy for countries in the “West” (Minorities at Risk codings)
is significantly negative, but this dummy is highly correlated with per capita income, making
it difficult to assign the effect. In the coding we use, “North Africa and Middle East” includes
the countries of the Arabian peninsula, the northern edge of Africa (Sudan is not included),
Cyprus, Turkey, Syria, Iraq, Iran, Israel, and Jordan.
24
able measuring the percentage of Muslims in each country in place of the regional
dummy, we find that although the sign of the estimated effect is as expected by
Huntington, it is not statistically significant by the usual standards (p < .12).
The reason is that there are a good number of countries with large numbers
of Muslims in subSaharan Africa and Asia that have seen little internal war.
In these regions, the correlation between percentage of Muslims and the log of
post-79 deaths is statistically zero (.03).40
Not surprisingly, a dummy variable for countries with 90% or more Muslims is strongly significant when included in model 1 in place of the regional
dummy. But it is so highly correlated with the region variable that there is not
enough evidence to sort out whether this “explains” the effect estimated for the
region variable (if both are included, neither is statistically significant). And
even if it did, it is unclear what the theory is. If Islam is somehow “violence
prone,” the effect should show up in the percentage-of-muslims variable, not in
a variable marking nearly homogenous Islamic societies.
Huntington also argues that countries with high proportions of young
males are especially at risk of civil violence, and suggests that this is part of the
explanation for higher levels of violence in muslim countries. Using World Bank
data on the percentage of 15-to-24 year old males in 1980, we found no clear
support for this argument. Although the countries of this region do have a more
youthful profile than one would expect on the basis of per capita income alone,
percentage-of-young-males is insignificant when added to model 1 (p = .25),
and the coefficient on the North Africa/Middle East dummy falls only slightly.
In some specifications, percentage-of-young-males can be significant (and positively related to civil violence) when the regional dummy is dropped, but this
is due to its high correlation with per capita income (.7 with logged income in
1980) rather than it picking up the regional effect. In conclusion, then, it is
possible that percentage-of-young-males is an independent causal factor, but it
almost surely does not explain the high average violence levels in the Middle
East and it will take better data to learn how to apportion influence between
this and other things that per capita income may stand for.
A final conjecture is that states in this region are more prone to violence
because many are oil-exporters. For example, Collier and Hoeffler (1999) argue
40 We coded the variable for percentage of Muslims ourselves, using data from the CIA
Factbook, Library of Congress Country Studies, and some country-specific sources for a few
difficult cases.
25
that natural resources such as oil inspire “greed”-based rebellions. We would
argue for multiple effects. On the one hand, oil revenues give a state resources
with which to fight insurgents. On the other hand, as Chaudhry (1997), Karl
(1997), and others maintain, oil-producers tend to have weaker state apparatuses than one would expect given their level of income because the rulers have
less need of a socially intrusive and elaborate bureaucratic system to raise taxes
(the so-called “Dutch disease”). Thus, if we control for per capita income, we
should find that oil exporters are more prone to internal war because their states
are weaker than one would expect given their income level.
When we add a dummy for oil exporters to model 1, we find that oil
exporters had three times more deaths from civil war after 1979 than did otherwise similar non-oil exporters.41 This result is not very robust across different
measures and specifications of the dependent variable, however. The odds that
an oil-exporter has an IISS civil war after 1980 is estimated as 2.3 times that of
a non-oil exporter, but this estimate might well be positive due to chance. The
results are somewhat weaker still when we use the SF data, both for the deaths
and the dichotomous measures of civil violence.
In addition, the dummy varible for countries in North Africa and the
Middle East remains significant with little change in the estimated effect even
after inclusion of the variable for oil exporters. So while it may be the case that
“Dutch disease” is associated with more domestic rebellion and violence than
one would expect given income levels, this does not seem to explain the high
levels of internal war in this region.
6. Three measures of ethnic diversity appear unrelated to either the probability or level of civil violence in our sample, once we control for income and
income growth. We have considered the following measures of ethnic/linguistic
diversity.
(a) Ethnic fractionalization, a commonly used measure derived from the
1964 Soviet ethnographic atlas (Sov 1964). Substantively, it is the probability
that two randomly drawn individuals are from different ethnic groups.42 The
The probability that the estimated coefficient is zero is less than .01 in a two-tailed test.
For the variable we updated and completed the World Bank list of oil exporters, using CIA
Factbook information where necessary.
41
For the former Soviet republics we computed the measure using the data from the 1989
Soviet census (Bremmer and Taras 1993). For the former Yugoslav republics we used the
42
26
use of data from prior to 1980 is appropriate since the perception of ethnic
divisions is in part endogenous to political conflict. From this perspective –
and contrary to the usual approach of treating ethnic composition as wholly
exogenous – it is appropriate that the the Soviet geographers coded Somalia as
highly homogenous in 1960 (for instance). We view it as “ethnically divided”
only since the fractionalization of clan families that occurred in the course of
the civil war.
(b) The population share of the largest ethnic group (which is difficult and
somewhat arbitrary to identify for some countries). Our version, based mainly
on data from the CIA Factbook and Encyclopedia Brittanica, is correlated with
fractionalization at .72 and yields the same results.43
(c) The (log of the) total number of spoken languages in the country as
coded by Grimes and Grimes (1996), which is correlated at .50 with fractionalization, yields the same results.44
It has been suggested that the relationship between ethnic fractionalization and civil violence should be nonmonotonic, with little violence for both
highly homogenous and highly heterogenous countries (Horowitz 1985). Perhaps the strongest argument is that a highly heterogenous country is strategically similar to a highly homogenous one, in that very small ethnic groups
will have to form coalitions to have political influence, and there are a great
many possibilities for cross-cutting and future shifts in coalition memberships.
Although a few studies have found some evidence for this prediction (cites ..),
we find none here, using any of the three different measures of the dependent
variable. The square of ethnic fractionalization (or any of the measures) is not
significant when added to the regression, though the effect is in the predicted
direction.45
data given in (Woodward 1995, 33-35). The effective number of ethnic groups (ENEG =
1/(1-fractionalization)) is easier to interpret but also has much more skewed distribution
than the fractionalization measure. No results change if we use ENEG instead.
Nor did we find evidence that countries with a plurality group between 40 and 80 or 90
percent of the population were more prone to violence, as do Collier, Eldabawi and Sambanis
(1999), or greater than 80%, as did Ellingsen (2000).
43
44 We include languages spoken by foreign guest workers when they number at least 1000
according to this source. Incidentally, the mean and median number of languages for the
sample are 54 and 20, with Papua New Guinea taking the prize at 827.
45
We suspect that some of the positive results found in the other studies may be due to the
27
7. We coded a variable marking the presence of religious minorities greater
than 5% of the population, distinguishing between “small” sect differences (e.g.,
Catholic/Protestant), “large” sect differences (e.g., Orthodox/Western Christian, Sunni/Shia), and different world religions (e.g., Hindu/Buddhist).46 No
way of combining or dividing these distinctions yields anything close to a significant relationship to the occurrence or magnitude of civil violence. This nonfinding is highly “robust” across different measures of the dependent variable
and different specifications.
8. At present, the most commonly used cross-national measure of democracy is the difference between the democracy and autocracy scales in the Polity
III data set. When we add the country average of this measure over the period
1960 to 1979 to model 1, the estimated coefficient has the sign predicted by the
nationalism script (-.048) and just manages significance at the 10% level (see
model 7). Excepting per capita income, whose estimated effect falls by about a
third, the other effect estimates change little.
This result is fragile, however, in two respects. First, it is highly sensitive
to different measures of civil violence and different model specifications, whereas
the other variables – including per capita income, with which the democracy
measure mainly “competes” due to high correlation – are much less so. The
democracy variable is thoroughly insignificant when we use the dichotomous
version of the IISS measure. It is insignificant with the wrong sign when we
use the State Failure project measures (dichotomous and continuous). It is
insignificant when we try breaking the 20-point scale into three dummy variables
(< −5, > −6 but < 6, > 5), which indicates that results with the Polity
measure depend on the arbitrary specifics of how it sorts countries not judged
highly democratic or highly autocratic.47 It is insignificant when we measure
per capita income in 1979 rather than 1960. When we looked at the measure
influence of the outlier Tanzania.
We used mainly the CIA Factbook (C.I.A. 1999) and Library of Congress Country Studies
(available on the web) for these codings, supplemented with country specific sources when
necessary. For subSaharan countries, we coded only Muslim/Christian differences, ignoring
estimates on sect differences within Christianity and the percentage of “indigenous” or “animist” beliefs, which we view as unreliable and conceptually problematic for this region. The
data are assessed for the 1990s, so one might have worried a little about civil violence causing
the perception of new religious cleavages if we had found anything.
46
Measures of democracy tend to agree on the most and least democratic countries, but
disagree on the (typically smaller) number coded as partially democratic. See below for more.
47
28
in particular years prior to 1980 rather than averaging over the 1960 to 1979
period, we found the results to be quite volatile depending on the year chosen,
and never significant when we controlled for income in 1979. Finally, when we
control explicitly for levels of civil war between 1960 and 1979, neither per capita
income nor the democracy measure has a statistically significant coefficient,
although the democracy measure fairs worse.
Second, the results on democracy depend on the specific measure employed. When we use the 1960-79 average of Alvarez et al.’s (1996) dichotomous measure, the estimated effect is insignificant regardless of which measure
we use (and has the wrong sign with the IISS measures; see model 8). This
is particularly telling because, at least for our purposes here, this measure is
theoretically more appropriate than the Polity measure used by most analysts
of civil war to date. Alvarez et al. code a minimalist notion of democracy
that asks whether the highest executive and the legislature (if any) are filled
by competitive elections. The Polity measure, by contrast, aggregates a variety
of features of political competition in a country, some of which may implicitly
define a country with a civil war as less “democratic.” For example, one component asks whether “changes in the chief executive occur through forceful seizures
of power” (XRREG). Another (PARREG) asks if competition among “enduring
political groups” in the country is “intense, hostile, and frequently violent,” and
still another (PARCOMP) judges political participation “competitive” if competition among enduring political groups “seldom causes widespread violence
or disruption”! If countries with civil violence are by definition “undemocratic”
or “less democratic,” then it is absurd to interpret a negative coefficient on the
Polity measure of democracy as indicating that less democracy causes more civil
war. By coding only on the presence of competitive elections, the Alvarez et al.
measure is much less likely to confound dependent and independent variables.48
Several authors argue that we should expect civil violence to be greatest at
medium levels of democracy, since grievances might be low in highly democratic
countries while the opportunity to express them might be minimized in highly
authoritarian polities. Adding squared versions of our democracy measures to
the models, we find no support for this conjecture here.
Regression of the Polity measure on the Alvarez et al. measure bears out the suggestion
that the Polity measure tends to code as nondemocratic states where bad things happen. For
example, Polity judges Colombia relatively undemocratic and Malaysia, Singapore, and Fiji
relatively democratic, whereas the Alvarez et al. measure takes the opposite view.
48
29
9. If federal constitutions allow greater self-government for regionally
concentrated minorities, then the nationalism script would imply that, other
things equal, federally organized states should have lower levels of civil violence.
“Other things equal” may be problematic, since the presence of factors making
civil unrest likely might make a state more likely to adopt a federal constitution
in the first place (e.g., India). With this caveat in mind, we added a measure of
each state’s degree of federalism in 1980 to model 1 and found it to be entirely
irrelevant. The other effect estimates are unchanged, partially excepting that for
country population, which is positively correlated with federalism. So although
these data does not allow us to rule out that the federal states might have had
even more civil violence if not for their constitutions, we can say that federalism
did not make them more peaceful than the unitary states on average.49
6.3
Additional variables, missing data, and alternative approaches
to the estimation
Kaplan (2000) has suggested that rapid population growth increases the likelihood of civil violence. Using the annual population growth rate from 1960 to
1979, we find that fast-growing states in this period were no more likely to have
civil wars since 1979, after controlling for the other factors. Other variables
that might measure resource scarcity and competition, such as population density and arable land per capita, are likewise insignificant (though in all cases the
sign is in the expected direction).
Collier and Hoeffler (1999) found that primary product exports as a percentage of GDP and average years of schooling in the population outperformed
per capita income in their probit analysis of civil war onsets between 1965 and
1995.50 They interpret primary product export share as a rough measure of
Our measure of federalism was constructed by Downes (2000), and consists of the number
of ‘yes’ answers to the following questions: Is the state called federal in its constitution?
Does the state have a legislative chamber representing federal units? Does the state require
approval of the upper house for constitional amendment? Is approval of federal units required
for constitutional amendment? Do regions have a directly elected executive? Do regions have
directly elected legislature? Our results did not differ when we used the answer to the first
question alone.
49
In fact, Collier and Hoeffler (1999) find an effect for both primary product export share
and its square, but because relatively few cases fall on the downsloping side of the parabola,
they interpret the result as a positive effect of export share on the probability of civil war. We
50
30
“lootable” resources (cf. hypotheses 5 in section 4 above) and average years of
schooling as a measure of the economic opportunity cost of becoming a rebel.
We find that the share of the population with a primary education in 1970 is
statistically unrelated to our measures of post-79 civil strife after controlling for
income, as is the export share of primary products in 1970 (which has a negative
sign when added to models 1 and 3). The export share in 1980 is significantly
related when added to model 1 (p < .04), but this disappears with different
measures of civil war and slight changes to the model specification. From looking at the cases, our impression is that primary product export share cannot be
taken seriously as a measure of lootable natural resources like drugs, diamonds,
and timber; instead, it seems to pick out economies that depend heavily on cash
crops or oil production. We suspect that it is in effect another proxy for state
coercive capacity that may happen in particular specifications to perform well.
We also tested whether political instability prior to 1980 was associated
with higher levels of civil violence afterwards. The number of nonconstitutional
leadership changes in a given period is plausibly a measure of state coherence
and strength, and thus, by the arguments in section 4, would be expected to predict civil war.51 Unfortunately, since civil violence is sometimes a consequence
of struggles for state leadership, and since a civil war can plausibly increase
the risk of leadership change, a variable measuring the number of nonconstitutional leadership changes between 1960 and 1979 could also proxy for unrelated
omitted variables that make a country more prone to civil violence.
We find that the number of nonconstitutional leadership changes from
1960 to 1979 is indeed positively related to measures of civil violence, but generally not significant. Closer inspection reveals that four of the six states with
more than five nonconstitutional successions had no civil violence, and these
cases exert a large influence because the distribution is right-skewed. An alternative measure – whether a state had at least one nonconstitutional succession
between 1960 and 1979 – is strongly significant in models 1-4 for all measures
of the dependent variable. Whether this is because this is a good measure of
suspect that the squared term is “fitting” a few outliers and thus wonder about the robustness
of their results on this variable.
In addition, various arguments hold that there should be a direct causal effect of political
transitions on the propensity for civil war; see, for example, Posen (1993), and Fearon (1998).
Our measure derives from Alvarez et al.’s regime data; it is essentially the number of changes
of the head of state while the country was not a democracy, corrected for constitutional
successions in monarchies, emirates, and communist states.
51
31
state coercive capacity is unclear, however, since the effect weakens considerably
when we include logged deaths from 1960 to 1979, or use the residuals of the
variable after “extracting” deaths prior to 1980.
A final issue concerns missing data. Not surprisingly, the World Bank
and the Penn World Tables tend not to have economic data for states that have
had intense civil wars, such as Lebanon, Afghanistan, Vietnam, and Cambodia.
This raises a concern about selection bias. To check this, we used the COW data
on countries’ total energy consumption by year to estimate per capita income
and income growth values for as many missing countries as we could.52 This
raised the sample size for models 1-4 and in Table 3 to 147, while significantly
improving the fit of the model (estimated coefficients change little, all t-statistics
increase, and the overall R2 rises to .37 in model 1).
7
Conclusion
The prevalence of internal war in the 1990s is for the most part the result
of a steady accumulation of protracted conflicts since the 1950s rather than
a sudden change associated with a new, post-Cold War international system.
Decolonization in the 50s and 60s gave birth to a large number of financially,
bureaucratically, and militarily weak states. These states have been especially
at risk for civil violence for the whole period, almost entirely in the form of
insurgency, or rural guerrilla warfare. Insurgency is a mode of military practice that can be harnessed to various political agendas, be it communism in
Southeast Asia and Latin America, Islamic fundamentalism in Afghanistan, Algeria, or Kashmir, right-wing “reaction” in Nicaragua, or ethnic nationalism in
Sri Lanka, Turkey, Rwanda, Burundi, Sudan, Ethiopia, Indonesia (E. Timor,
Aceh), India (the northeast, the Sikh insurgency) and more. The conditions
that favor insurgency – in particular poverty and slow economic growth, which
favor rebel recruitment and mark weak states – appear to be better predictors
of which countries are at risk for civil war than are indicators of ethnic and
religious diversity.
What about group grievances? The nationalism script’s argument that
We regressed log of per capita income on log of per capita energy consumption (clustering
standard errors by country) and then used this to predict missing per capita income figures.
Energy consumption is a good proxy for national income; see xxx.
52
32
discrimination and oppression along cultural lines produces angry groups that
will support violent redress seems almost overwhelmingly compelling. If we
moved our analysis to the group level, would we find that measures of group
grievances help predict violence with the state? Thus far, our analyses of the
Minorities at Risk (MAR) data set answer this question in the negative (Fearon
and Laitin 1999; Laitin 2000). The MAR measures of relative economic disadvantage and of economic, language and other cultural policies that discriminate
against the minority do not help one pick out which groups will be involved in
rebellions with their states. Further, parallel to our findings here, measures of
the linguistic distance between minority and dominant group are insignificant.
These measures may not be very good, and criteria by which groups were selected for the MAR sample may bias the analysis against finding an effect for
grievances, cultural differences, and levels of state discrimination.53 Further research may find some impact for such factors, but at least we can say that there
is no powerful and clear relationship between internal war and culturally distinct
minorities subject to discrimination. For every such group engaged in a violent
fight with the state, there are many other culturally distinct, discriminatedagaint groups that are not. Future research needs to focus on the conditions
under which ethnic and other grievances translate into destructive civil wars.54
We have argued that viewing “ethnic wars” as a species of insurgency helps
explain the apparent insignificance of ethnic and religious diversity and, perhaps,
discrimination as predictors of civil violence. If, under the right environmental
conditions, just 500 to 2000 active guerrillas can make for a long-running and
highly destructive internal war, then the average level of grievance in a group
may not matter that much. What matters is whether active rebels can hide
from government forces and whether economic opportunities are so poor that
the life of a rebel is attractive to 500 or 2000 young men. Grievance may favor
rebellion by leading nonactive rebels to help in hiding the active rebels. But we
have argued that all the guerrillas really need is superior local knowledge to the
government’s, which enables them to threaten reprisal for denunciation.
Another reason that discrimination may be unrelated to violence is that
governments will choose to discriminate most against the groups that are least
able to sustain a rebellion, such as Roma, many urban-based minorities, or
53
MAR groups are at least indirectly sampled on the dependent variable.
The one group-level variable in the MAR data that robustly distinguishes groups involved
in rebellion is a measure of regional concentration, consistent with hypothesis 3a in section 4
above.
54
33
Kosovan Albanians in Yugoslavia before the KLA obtained weapons from the
1997 disorder in Albania. Collier and Hoeffler (1999) usefully observe that a
grievance-based rebellion would face significant collective action problems, in
contrast to a greed-based rebellion. We would add, however, that solving this
collective action problem would not necessarily imply war. Instead, it could
yield a common minority front for bargaining with center and the in-group
policing of extremists. Indeed, insurgency is often better understood not as a
success of collective action but as a failure by the nonrebels to police their own
extremists (Fearon and Laitin 1999).
8
Appendix
In a Nash equilibrium of the game described in the text, G chooses c to minimize
βm(1 − p(c, α)) + c, where m is the expected number of rebels. Given m, G’s
marginal benefit of increasing c is βmp1 (c, α), which decreases with c, while
the marginal cost is 1. So the optimal c∗ is zero when p1 (0, α) ≤ 1/βm (since
p11 < 0) and is the unique solution to p1 (c, α) = 1/βm otherwise (unique
because the left-hand side strictly decreases and approaches zero as c grows
large).
In a Nash equilibrium the population correctly anticipates c∗ , and thus
m = nF (b − (b + d)p(c∗ , α)). This suffices to show that in the unique Nash
equilibrium c∗ = 0 when
1
p1 (0, α) ≤
(1)
βnF (b)
∗
and is the solution to
p1 (c, α) =
1
βnF (b − (b + d)p(c, α))
(2)
otherwise.
Proof of Proposition: (a) Let ĉ(α) solve p(ĉ(α), α) = b/(b + d). (ĉ(α) exists since
p(c, α) is continuous, p(0, α) = 0 and limc→∞ p(c, α) = 1.) The assumption that
limα→0 p(c, α) = 1 for all c > 0 implies that limα→0 ĉ(α) = 0. c∗ (α) ≤ ĉ(α)
since otherwise G could spend less and still deter all from rebelling. Thus, the
“sandwich theorem” for limits implies the conclusion that limα→0 c∗ (α) = 0.
(b) Since limα→∞ p1 (0, α) = 0 and limα→0 p1 (0, α) = ∞, there exists an
34
α = ᾱ such that p1 (0, ᾱ) = 1/βnF (b). For all α > ᾱ, equation (1) holds. Q.E.D.
Claim: ∂c∗ /∂n > 0, ∂m∗ /∂n > 0, and ∂(m∗ /n)/∂n < 0.
Proof. Treating (2) as an identity in n and differentiating both sides yields
∂c
∂c
= −[βnF (·)]−2 [βF (·) − βnf (·)(b + d)p1 (c) ].
(3)
∂n
∂n
Using p11 < 0 and p1 > 0, the assumption that ∂c/∂n ≤ 0 yields the contradiction that the left-hand side is zero or positive while the right-hand side must
be negative. Thus ∂c/∂n > 0. Since m∗ = nF (b − (b + d)p(c∗ )), ∂m∗ /∂n is just
the second term in brackets on the right-hand side of (3). This is positive given
∂
that ∂c/∂n > 0. ∂(m∗ /n)/∂n = ∂n
F (b − (b + d)p(c∗ )), which is negative since
∂c/∂n > 0. Q.E.D.
p11
Claim: Consider a c.d.f F 0 (y) such that F 0 (y) < F (y) for all y (that is, F 0
represents an upward shift in the distribution of income). Let (c, m) be the
Nash equilibrium of the game given F , and (c0 , m0 ) the Nash equilibrium given
F 0 . Then c0 < c and m0 < m.
Proof: From (2) we have that
p1 (c)βnF (b − b(b + d)p(c)) = p1 (c0 )βnF 0 (b − (b + d)p(c0 )).
If (to the contrary) c0 > c, this equality cannot hold, since then p1 (c0 ) < p1 (c)
and F 0 (b − b(b + d)p(c0 )) < F (b − (b + d)p(c)). The equality holds only if c0 < c
and nF 0 (b − b(b + d)p(c0 )) < nF (b − (b + d)p(c)), which implies further that
m0 < m. Q.E.D.
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38
Dep. Var. =
Model # =
Income
Growth
Ctry. Pop.
Fr. Colony
N.Afr/ME
const.
N = 137
IISS deaths
(1)
β
s.e.(p)
-0.75 0.17 (.00)
-0.34 0.08 (.00)
0.26 0.09 (.01)
-1.29 0.41 (.00)
1.44 0.49 (.00)
2.79 1.91 (.15)
R2 = .27
(OLS)
Model # =
β
-0.72
-0.33
0.20
-1.21
1.27
-0.72
Income
Growth
Ctry. Pop.
Fr. Colony
N.Afr/ME
Flat
Eth. Frac.
Min. Relig.
Min. Sect.
DemAut68
Prze6079
const.
3.52
N
=
R2 =
Table 1
IISS war?
SF deaths
SF war?
(2)
(3)
(4)
β
s.e.(p)
β
s.e.(p)
β
s.e.(p)
-1.24 0.31 (.00) -0.74 0.14 (.00) -1.33 0.33 (.00)
-0.41 0.13 (.00) -0.26 0.06 (.00) -0.46 0.14 (.00)
0.69 0.17 (.00) 0.34 0.07 (.00) 0.70 0.18 (.00)
-1.12 0.62 (.07) -1.35 0.33 (.00) -2.58 0.77 (.00)
1.46 0.80 (.07) 1.47 0.39 (.00) 2.96 0.88 (.00)
-1.98 2.94 (.50) 1.28 1.52 (.40) -1.79 3.14 (.57)
chi2(5) = 46
R2 = .36
χ2(5) = 53
(Logit)
(OLS)
(Logit)
Table 2
Dep. Var. = IISS deaths, OLS
(5)
(6)
(7)
(8)
s.e.(p)
β
s.e.(p)
β
s.e.(p)
β
s.e.(p)
0.17 (.00) -0.76 0.19 (.00) -0.49 0.22 (.03) -0.57 0.24 (.02)
0.08 (.00) -0.33 0.08 (.00) -0.39 0.08 (.00) -0.39 0.08 (.00)
0.10 (.04) 0.25 0.09 (.01) 0.25 0.10 (.01) 0.28 0.10 (.01)
0.41 (.00) -1.24 0.41 (.00) -1.51 0.43 (.00) -1.38 0.42 (.00)
0.50 (.01) 1.71 0.51 (.00) 1.33 0.51 (.01) 1.48 0.50 (.00)
0.38 (.06)
0.86 0.57 (.13)
-0.57 0.35 (.11)
-0.10 0.37 (.78)
-0.05 0.03 (.09)
0.45 0.50 (.37)
1.93 (.07) 2.80 2.07 (.18) 0.94 2.11 (.66) 0.85 2.55 (.74)
137
133
118
118
.29
.30
.32
.31
39
liis6079
Income
Growth
Ctry. Pop.
Fr. Colony
N.Afr/ME
Flat
const.
N = 137
Var. Name
IISS deaths
SF deaths
IISS war?
SF war?
liis6079
Income
Growth
Ctry. Pop.
Flat
French Col.
N. Afr./M.E.
Eth. Frac.
Min. Relig.
Min. Sect
DemAut68
Prze6079
IISS deaths
β
s.e.(p)
0.37 0.08 (.00)
-0.45 0.16 (.01)
-0.31 0.07 (.00)
0.05 0.09 (.57)
-0.77 0.37 (.04)
1.07 0.45 (.02)
-0.59 0.34 (.08)
4.35 1.72 (.01)
R2 = .44
(OLS)
Table 3
IISS war?
β
s.e.(p)
0.36 0.17 (.04)
-1.08 0.32 (.00)
-0.39 0.14 (.00)
0.55 0.18 (.00)
-0.67 0.63 (.29)
0.94 0.82 (.25)
-0.41 0.64 (.52)
-0.23 3.05 (.94)
chi2(7) = 55
(Logit)
SF deaths
β
s.e.(p)
0.48 0.09 (.00)
-0.42 0.13 (.00)
-0.24 0.05 (.00)
0.14 0.07 (.05)
-0.99 0.28 (.00)
0.91 0.35 (.01)
-0.48 0.26 (.07)
2.30 1.34 (.09)
R2 = .53
(OLS)
SF war?
β
s.e.(p)
1.18 0.42 (.00)
-1.04 0.38 (.01)
-0.44 0.15 (.00)
0.44 0.20 (.03)
-2.23 0.86 (.01)
1.51 0.97 (.12)
-1.78 1.13 (.12)
0.78 3.42 (.82)
χ2(7) = 79
(Logit)
Table 4: Variables
Description (see text for sources and other variables)
Log of civil war deaths, 1980-99, IISS/Sivard data
same, but with State Failure project data for 1980-96
‘1’ for countries with IISS/Sivard wars in 1980-99
same, with SF data for 1980-99
IISS deaths, but measured 1960-79
Log of per capita income in 1960
Annual growth rate of per capita income, 1960-79. (In Tables 1 and 2
the “effect” of liis6079 has been taken out – see text)
Log of country population in 1965
‘1’ for countries in which the difference between the highest and lowest
elevations are less than 1000 meters
Former French colony
Country in North Africa/Middle East region
Ethnic fractionalization, based on the 1964 Soviet Ethnographic Atlas
‘1’ for countries with at least one minority greater than 5% of population that predominantly subscribes to a different world religion from
the majority religion(s)
Same as Min.
Relig, except including difference of sect (e.g.,
Catholic/Protestant, Sunni/Shia)
Average over 1960-79 of the difference between Polity III democracy
and autocracy measures
Average over 1960-79 of the Alvarez et al. (1996) democracy measure
40