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Discussion Papers
Department of Economics
University of Copenhagen

No
...
, Denmark
Tel
...
econ
...
dk

ISSN: 1601-2461 (E)

When does ethnic diversity lead to violence? Evidence from the 2007 elections in Kenya

July 2011

Thomas Markussen
Department of Economics, University of Copenhagen

Kitavi Mbuvi
Kenya Institute of Education

Abstract
Exploiting a district level data set on the 2007/8 post-election violence in Kenya, this
paper investigates why polarization between ethnic groups results in violent conflict in
some cases, but not in others
...

Violence occurred more often and with greater intensity in areas characterized by a
high level of polarization between the Kikuyu ethnic group and other ethnic
communities
...
The paper
attempts to explain why in areas with similar levels of ethnic polarization, a flawed
election process produced so different reactions
...
On the other hand, there is little evidence that clashes resulted from
land inequality, land pressure or political competition
...
Introduction 1
Twenty six years after the publication of Donald Horowitz’ seminal book, “Ethnic Groups in Conflict”,
ethnic violence remains a central issues on the international agenda, as exemplified by recent events
in Kyrgyzstan, Darfur, Cote d’Ivoire and elsewhere
...
This paper exploits a data set in on the incidence and intensity of violence following
the 2007/8 elections in Kenya to investigate why tensions between ethnic groups sometimes, but
not always, lead to violent conflict
...
The violence followed a clear
ethnic pattern, as it mostly pitted members of the Kikuyu tribe against members of different tribes
from Western and Coastal Kenya
...
In other words, similar levels of
ethnic polarization led to violence in some areas but not, or to a much lesser extent, in others
...

Results show that ethnic violence was triggered by poverty, unemployment among young males, and
decrease in access to essential, public services (in particular, access to piped water)
...
The effects of ethnic
diversity have been studied intensely in this literature
...
On the other hand, Montalvo and Reynal-Querol
1

We are grateful for very useful comments and other inputs from Anne Christensen, Jørgen Elklit, Markus
Goldstein, Jane Kabubo-Mariara, Kawawa Masumba Kilango, Samuel Kipruto and Johan Mistiaen
...
All
remaining errors are our own
...


2

(2005) argued that conflict is not driven by fractionalization (the coexistence of many, relatively
small groups) but rather by polarization (the coexistence of a few groups of similar size) and found a
significant, positive effect of polarization on the probability of a country experiencing civil war
...
In this regard it resembles Sambanis (2001) who also investigated the specific
drivers of ethnic-, as opposed to “revolutionary” or other types of wars
...
The paper most closely related to ours is the contribution by Dercon and
Gutierrez-Romero (2010), who exploit a household level data set to investigate the triggers of the
2007/8 post-election violence in Kenya
...
The present
study, conducted at the district level, complements Dercon and Gutierrez-Romero’s paper, both
because studies at different levels of aggregation each have distinct advantages, and because the
variables included in the analyses are quite different
...
The key question asked
here, why did Kikuyu-non-Kikuyu ethnic polarization lead to much more violence in some areas than
in others, is not asked by Dercon and Gutierrez-Romero
...
Section 3 discusses theory and presents hypotheses to be tested
...
Section 6
presents regression results
...

Section 7 concludes
...
Background
2
...
However, ethnic and political
violence was never completely absent
...
The rebellion was to a large extent
motivated by the desire to regain land confiscated for European settlement
...

From Independence in 1963, Kenyan politics was dominated by the influence of ethnicity
...
For example,
Nyerere promoted Swahili as a national language in Tanzania, while vernacular languages have
retained a much stronger role in Kenya
...

At the same time, Kenya is so ethnically fragmented that inter-ethnic coalition building is
always a necessary component of a strategy to secure a stable power base
...
Other important
groups include the Luo and the Kisii, mainly inhabiting Nyanza province on the brinks of Lake Victoria
(see Figure 1); the Luhya, who are most numerous in Western province; the Kalenjin, Maasai,
Turkana and Samburu, who regard different parts of Rift Valley province as their “ancestral
homelands”; The Meru and Embu who share important characteristics with the Kikuyu and inhabit
the central parts of Eastern province; the Kamba who dominate the Southern parts of Eastern
province; and the Mijikenda who are numerous in coastal areas (See Ng’ang’a 2006 for detailed
descriptions of each group)
...
Up to 1991, Kenya was de-facto a one-party
state, ruled by the Kenya African National Union (KANU)
...
M
...
In 1969, an significant episode of ethno-political
fighting occurred when Kenyatta supporters clashed with supporters of Luo leader Jaramogi Oginga
Odinga in Kisumu, a town in Western Kenya, resulting in 11 fatalities and many injuries
...
This, in combination with Moi’s fragile power base, consisting primarily of the
Kalenjin and other Rift Valley communities, arguably led to the rise of ethno-political violence in the
1990s
...
In practical terms, the likelihood of voting for the opposition was to a
large extent determined by ethnicity and consequently the victims of violence were mostly Kikuyus
and members of other groups who have migrated to the Rift Valley in the decades prior to and after
Independence
...
Moi
was not running
...
Kikabi campaigned on a platform of anti-corruption and reform and won in a
landslide
...
2 The 2007 elections
After the 2002 election, the multi-ethnic coalition behind Kibaki and the NARC movement
disintegrated
...
g
...
3 A new political force emerged, namely the Orange Democratic Movement (ODM),
headed by Raila Odinga, a Luo and son of Jaramogi Oginga Odinga
...
In response, Kibaki formed a new
party, the Party of National Unity (PNU)
...
Opinion polls taken before elections reveal
strong correlations between ethnicity and voting intentions (Kimenyi and Gutierrez-Romero 2008)
...
Voting proceeded in a largely peaceful manner on
December 27th
...
The first results showed a strong lead for
Odinga in the race for president
...
Hours after the announcement of this highly controversial outcome, Kibaki was sworn in as
President in a ceremony witnessed only by a few political backers and not broadcast on television
...

The memorandum was widely perceived as implying that Luo Leader Raila Odinga was to be nominated for a
newly established post of Prime Minister
...

2
...
In Nairobi, Mombasa, Kisumu and other urban
centers, angry mobs took to the streets
...
In the multi-ethnic slums of Nairobi,
ethnic-based fighting erupted and more than a 100 persons were killed
...
Most violence was of a “low-tech” nature, conducted mostly with
machetes (known in East Africa as “pangas”), clubs, bows and arrows
...

Between 300,000 and 600,000 persons were displaced as a result of the post-election
violence
...
By the definition applied by some studies (more than
1,000 battle deaths per year) this arguably places the conflict in the “civil war” category
...
For example, Sambanis requires that “the parties are politically and
militarily organized, and they have publicly stated political objectives” (p
...
This was not the case
in Kenya
...
Nevertheless,
comparisons between the results presented here and those from studies of the incidence and
severity of civil wars remain highly relevant
...
4 Settlement and aftermath
Throughout the conflict, the international community focused intensely on the violence in Kenya
...
In early March 2008, these
efforts finally bore fruit, as the parties reached an agreement to form a coalition government
...
The number of ministers and vice-ministers was expanded significantly and seats shared
between candidates from both sides
...

6

The settlement also called for inquiries into, respectively, election irregularities and postelection violence (see below), and for land- and constitutional reform
...
In a 2010 referendum, Kenyans adopted a new constitution, which,
among other things, is intended to strengthen local government and impose constraints on the
hitherto extremely powerful presidency
...

The sections below describe various aspects of the post-election violence in more detail
...
g
...


3
...
1 Greed and grievance
One powerful, conceptual framework for understanding the determinants of violent, civil conflict
was advanced by Collier and Hoeffler (1998, 2004)
...
In cross-country analyses of the onset and duration
of civil wars, Collier and Hoeffler find that factors most obviously related to greed are more robustly
correlated with the incidence of civil war than factors most obviously related to grievance
...
Similar conclusions are reached
by Fearon and Laitin (2003)
...
In particular, Collier and Hoeffler regard ethnic
fractionalization as a factor “most obviously related to grievances”, and consider it as a potential
determinant of civil wars, alongside other potential factors
...
The task we set ourselves is to determine why the effect of ethnic polarization
was much more devastating in some areas than in others
...
These factors are grouped according to the
greed/grievance dichotomy
...
2 Grievances
Two major, potential sources of group grievance in Kenya are a) land issues, and b) struggles over
access to state expenditure
...
Furthermore, the history
of land relations since colonial times has given rise to strong inter-ethnic tensions related to land,
especially in the Rift Valley
...
During British rule, large areas were expropriated for
European settlement
...
Around the time of Independence, the bulk of
the White Highlands shifted back into Kenyan hands
...
A large number of these outsiders were Kikuyus
...
Second, the Kikuyu wielded dominant political and economic power
at the center in Nairobi
...
This generated a
feeling of entitlement to compensation in the minds of some Kikuyus, such as the former Mau-Mau
fighters
...
Around
the time of Independence, some farms were simply given, or sold cheaply, from the European
farmer to his most trusted African employee
...
Among the
communities that consider themselves natives of the area, on the other hand, an important view has
been that the settlers were trading in “stolen goods”, since the British had originally paid no
compensation for occupying the White Highlands
...
g
...

Grievances related to land are proxied in this study by two variables
...
The gini coefficient of agricultural land holdings
among households in rural areas is used
...
Presumably, land inequality is a more potent source of conflict if, for
example, the largest farms are owned disproportionately by ethnic “outsiders”
...
Second, a measure of rural population density is used
...
Citizens
depend on the government for the provision of a number of essential, public goods, such as water,
sanitation, electricity, roads, schools, clinics and hospitals
...
Qualitative as well as
quantitative evidence suggests that the distribution of government spending is determined to a
large extent by ethno-political factors (e
...
Burgess et al
...
We assume that frustration is more
likely to result from absolute or relative decline in access to public goods than from low levels of
service provision
...
On the other hand, the change in access to services
experienced over recent years is directly linked to the policies of current and recent governments
...
Conversely, a decline in
access to electricity, water or other goods is likely to engender disappointment and frustration, even
if local levels of access remain relatively high, compared with other areas
...
Our measure of grievances
related to the distribution of public expenditure is the increase (positive or negative) in the share of
households with access to piped water into their dwelling between 1997 and 2005
...

Also, measures of access to water services are more readily comparable between the household
surveys available than measures of access to, say, electricity, schooling, roads or clinics
...
3 Greed
Ethnic polarization may explode into violence because of grievances over land or public resources,
especially when the allocation of land and public goods is perceived to take place according to
unfair, ethnic criteria
...
Polarization may only have turned violent because local political leaders, or
leaders of criminal gangs, saw the post-election period as an opportunity to reach certain targets by
means of violence
...
There is
even evidence that some perpetrators of violence were paid a piece rate fee for each hut they
burned down (Waki 2008, p
...
Also, it is well established that the Mungiki criminal network played
a very active part in organizing violence in Nakuru, Naivasha town and elsewhere
...
Of course, politicians and even gangsters
may simply have responded to demand from local populations, and this demand may be rooted in
the grievances discussed above
...
A politician may wish to engage in ethnic cleansing in order to drive out
groups traditionally backing political opponents
...
Land may be used as a patronage good
...
They may also have been able to exploit episodes of violence to recruit new members
...
Based on
this line of reasoning, we use a measure of unemployment among young males (the most likely
militia members) as a proxy for “greed”
...
The idea is that the incentive
for electorally motivated ethnic cleansing is higher in areas where elections are close
...
Studies of the determinants of civil
conflict typically find that per capita income is correlated with conflict
...
On the other hand, poverty also improves the recruitment possibilities for political
entrepreneurs, and may reduce the local state’s ability to respond to violence, because poverty is
typically associated with a low potential for taxation
...
Data
4
...
We exploit the data collected by the
Commission of Inquiry into Post Election Violence (CIPEV), better known as the Waki Commission,
named after its chairman, Justice Philip N
...
The Waki Commission was established as part of
the international-brokered agreement that ended the stand-off between government and
opposition in March 2008
...
The commission collected evidence on post-election violence from hospitals,
10

doctors, the Ministry of Medical services and the police
...
The commission concludes that 1,133 deaths resulted from the
post-election violence
...
First, the
Commission is perceived to have worked independently of government interference
...

The work and report of the commission was followed intensely by local media as well international
observers
...
In particular, the Commission advocated that a tribunal was
established in order to prosecute those bearing main responsibility for the violence
...
If the tribunal was not established by a set date, this list would be forwarded to the
International Criminal Court in the Hague
...
Second, an independent inquiry based on detailed
tracking of media reports finds a number of fatalities of roughly the same magnitude, namely 1,128
(Dercon and Gutierrez-Romero 2010)
...
Population data is taken from the 2008
Statistical Abstract of Kenya (Kenya National Bureau of Statistics 2008)
...


4
...
The most recently available, pre-2008 data on ethnic composition at the
district level is from 1989 Census
...
As a result of migration and differential
population growth rates, ethnic composition is likely to have undergone some change between 1989
and 2007
...
An additional source of error is generated

11

by the fact that some districts were split up between 1989 and 2007
...
4

4
...
This survey was conducted by the National Bureau of
Statistics in collaboration with the World Bank and other external donors
...
This gives an average of 191 households
(967 individuals) per district
...

First, the KIHBS data provides estimates of poverty
...
Poverty lines were defined according to standard
criteria, based on nutritional- and a limited set of non-food requirements
...
The workforce is defined as all individual between 15
and 64 who are not recorded in the survey as retired, home makers, full time students, incapacitated
or too sick to work
...
This is somewhat broader than the definition of
unemployment typically used in developed countries, since in this context typically only those who
seek work, but cannot find it, are defined as unemployed
...
When individuals are reported to be “doing nothing” rather than
“seeking work” it is more likely to result from very low prospects of actually finding a job than from a
lack of desire to work
...

Thirdly, the survey data is used to create a measure of land inequality
...
A
4

The 2009 Census also collected data on ethnicity
...


12

weakness of this measure is the failure to take the quality of agricultural land into account
...
However, most of this variation is arguably between- rather than
within districts, which reduces the importance of this source of error
...
Based on these two data sets, the percentage change in access to
private, piped water between 1997 and 2005 is calculated
...
4 Election data
Data on the results of the 2007 elections were downloaded from the web site of the Electoral
Commission of Kenya, ECK (the ECK has since been dissolved and its website shut down
...
We aggregate data from the electoral constituency level to
the district level and create a measure of political competition by calculating the absolute difference
between vote shares for President Mwai Kibaki and opposition leader Raila Odinga
...
Indeed, as described above, a main trigger of the violence was the
perception that they are not
...
Most cheating
seems to have taken place in the “heartlands” of each of the main contenders, Kibaki and Odinga
...
Neither the Kriegler Commission nor
other bodies have attempted to produce a “corrected” list of election results
...
Descriptive statistics and estimation strategy
Figure 2 shows that the violence was concentrated in the South Western part of Kenya, and in
Nairobi and Mombasa
...
However, we believe
that the most relevant type of comparison is between the violence-struck districts and other districts
in the same part of the country
...
Also, the presence of the state in several of these districts is very limited
...
Therefore, our
preferred estimation sample includes only the districts were killings occurred, and the districts
bordering these
...
Therefore,
the predominantly urban districts of Nairobi, Mombasa and Kisumu are excluded in most analyses
...

The determinants of post election violence are investigated in this paper with the use of
regression analysis
...
This assumption does not strictly hold in the present context
...
We nevertheless continue
...
For
example, the cross-country data sets used to investigate the causes of civil war are in many cases
characterized by spill-over effects from conflict in one country to conflict in another
...
There has been much debate about
whether the violence was “spontaneous” or “planned”
...
However, no evidence indicates that leaders organized violence outside their
“own” areas
...
Also,
violence erupted in most districts very quickly after the announcement of presidential election
results on December 30th
...
Hence, violence did
not in general spread gradually from one district to another
...
While the districts affected by post-election violence are contiguous, with
the exception of Mombasa, see Figure 2, the intensity of conflict varied widely within this area
...
The three districts with the highest
number of killings (Nairobi, Nakuru, Uasin Gishu) do not border each other
...
In linear
regressions, autocorrelation affects statistical inference, but not point estimates
...

Most spill over seems to have occurred within provinces (for example, the killings in Nakuru and
Naivasha towns were to an important extent reactions to killings elsewhere in the Rift Valley)
...

Furthermore, in one robustness test we also allow errors to be correlated across districts
neighboring each other, using the so-called “spatial error model”
...
In this model, violence in district i is assumed to depend on average levels of violence in
neighboring districts (Anselin 1988)
...
As described above, there is a history of ethno-political violence in
Kenya, especially in the Rift Valley
...
Also, the intensity of violence experienced in 2007/8 was
unprecedented
...
For example, anticipated conflict may lead to
lower investment and therefore to higher poverty and unemployment
...
Since the conflict was
unanticipated by most people, these problems are in fact likely to be of minor importance
...
1 Ethnic polarization
As mentioned above, many quantitative studies of ethnicity and violent conflict have used the
ethno-linguistic fractionalization index (ELF) as the key measure of ethnic diversity (e
...
Colier and
Hoeffler 1998, Fearon and Laitin 2003)
...
5 Measures such as these are highly useful for studying,
for example, the overall picture of civil conflicts across countries or across long stretches of time
...
In fact, in most specific conflicts, some fault lines are
much more salient than others
...

5

The ELF index is defined as 1 −

∑s

2
i

, where si is the share of ethnic group i the total population
...
The RQ index was the measure of polarization used in Montalvo

i 
2

index is defined as 1 −

and Reynal-Querol 2005
...
Kikuyus have migrated out of their “ancestral” area to a
higher extent than most other groups and have mostly been economically successful where they
have settled
...
Finally, the 2007
Presidential election was perceived by many to have been stolen by the incumbent, Kikuyu
president, Mwai Kibaki
...
In many places, Kikuyus were attacked by members of
other groups, mostly from Western Kenya
...
To be sure, this is not the full
picture
...
On the Coast, Kambas and other
upland communities were targeted along with Kikuyus
...
For this reason, the measure of
ethnic polarization applied in this study is an indicator taking the value one if the share of Kikuyus in
the district population is larger than five and lower than 95 percent, and zero otherwise
...
Conceptually, the measure is more closely related to ReynalQuerol’s polarization index than to the ELF, although in practice the correlation with the ELF index is

...
46
...

Now, the key observation made in this paper is that although violence was on average much
more intense in areas with Kikuyu-non-Kikuyu polarization, there were a number of areas where
Kikuyus co-existed with other groups and fatalities did not occur
...
In nine of these districts, no fatalities were reported as a result
of post-election violence
...
In all of these, Kikuyus lived side by side with
sizeable groups of Kalenjin, Luo or Luhya, all communities which heavily favored the ODM in the
elections and with which much fighting occurred in other districts
...
Therefore, as discussed in the introduction, the key question we ask is:
16

why did polarization between Kikuyus and non-Kikuyus explode into violence in some districts and
not, or to a much smaller extent, in others?
Table 1 presents summary statistics on the variables used in regression analyses below
...
The tables reveal very significant variation on all
the variables used
...
Killings per capita were significantly higher in the districts of Uasin Gishu and, to a smaller
extent, Nakuru than in other districts
...

Table 2 presents the matrix of bivariate correlations between the main variables used
...
The first column shows that the per capita number of killings during the
post-election violence was significantly correlated with Kikuyu-non-Kikuyu polarization, male youth
unemployment and land inequality
...
In particular, the correlation between poverty and intensity of violence is insignificant,
and the point estimate is negative
...
g
...
Do and Iyer’s study of the Maoist insurgency in Nepal also finds that poorer districts were
more exposed to violent conflict than others (Do and Iyer 2010)
...
356, p=
...
Kikuyus have tended to migrate into areas with good economic
opportunities and therefore polarization is systematically higher in more affluent areas
...


6
...
Explanatory variables include the measures included in Table 2
...
Interactions between Kikuyu595 and the
17

other explanatory variables are therefore included
...

The simultaneous inclusion of several interactions between Kikuyu595 and other variables gives rise
to concerns about multicollinearity
...
6 As a rule of thumb, VIFs above 10 are often taken as indications of
excessive multicollinearity (Neter et
...
1989)
...
4, not far below the rule-of-thumb threshold of 10
...
In subsequent regressions, therefore,
insignificant variables are gradually removed from the model
...
86 in the last regression (adjusted R-squared =

...
The VIF gradually drops and reaches the value of 3
...

In all regressions in the table, three of the interactions with Kikuyu595 are significant at the 1
percent level, namely those with poverty, male youth unemployment and change in access to
private, piped water
...
The main effect of Kikuyu595 is significant in
three models, while none of the other main effects are significant
...
On the other hand, the hypotheses that land inequality,
population pressure and political competition were important conditioning factors behind the postelection violence are not supported
...
All regressions in this table are essentially permutations of
regression 4 in Table 3
...
Therefore, the potential effect of outliers on estimated coefficients is an important concern
...
To check whether results are driven by Uasin
Gishu, this district is removed in the first regression in Table 4
...
In the third regression,
the urban districts of Nairobi, Mombasa and Kisumu are included in the estimation sample
...


18

arguably meaningful, since the variables intended to measure grievances related to agricultural land,
population density and land inequality, are not included in this model
...

Since the dependent variable, killings per capita, is truncated at zero, a tobit model may be
viewed as more appropriate than Ordinary Least Squares (OLS)
...
However, regression 5 in table 4 presents results from applying a tobit estimator
...
Regressions 6 and 7 take account of this possibility by presenting results from,
respectively, a spatial error- and a spatial lag model (Anselin 1988)
...
In the spatial lag model, the
level of violence in district i is assumed to depend on the average level of violence in neighboring
districts
...

The Waki report distinguishes between killings by gunshot and other killings, and assumes that
killings were done by the police if an only if they happened by gunshot
...
Rather, much
police violence resulted from the brutal and clumsy attempt of the police force to control the
reactions of frustrated opposition supporters to the announcement of election results
...
From this perspective, the killings committed by
civilians were ethnically motivated in a stronger sense than the killings committed by the police
...
This is done in regression 7, where the dependent variable is
the per capital number of killings committed by civilians (i
...
by non-police perpetrators)
...
All other weights are zero
...


19

Finally, regressions 2 and 3 dealt with the potential problems of high outliers by excluding
extreme observations
...
This strategy is implemented in regression 8, where
the regressand is a dummy variable taking the value 1 if a district experienced at least 10 killings as a
result of post-election violence and zero otherwise
...
Therefore, the estimated effects of these variables
appear not to be artifacts of sample selection, influential outliers, spatial effects or choice of
estimator
...
59 or above)
...
1 Areas with Kikuyu-non-Kikuyu polarization
In the analyses presented above, hypotheses about triggers of ethnic violence were tested by
means of interactions terms between the measure of ethnic polarization (Kikuyu595) and other
variables
...
This is the approach taken in Table 5, which is based only on districts with Kikuyu shares
between five and 95
...
Tables 3 and 4 include province dummies
...
For this reason, and to save on scarce degrees of freedom, only an indicator for being in the
Rift Valley is included
...
In most analyses, Nairobi and Mombasa are excluded (Kisumu is not included in
the sample because it has less than five percent Kikuyus)
...
The result
is that, as in Tables 3 and 4, poverty, male youth unemployment and change in access to private,
piped water emerge as the most important determinants of violence
...
In regression 5, Uasin Gishu district is removed
...
In regression 7, Nairobi and Mombasa are
included
...
The inclusion
of Nairobi and Mombasa leads to a drop in the coefficient on poverty, which is now insignificant
...
A closer look at the variation in violence within these cities, however, does provide support
for the view that poverty drives violence
...
5)
...
67 in
regression 7 to
...

The last regression explores the effects of unemployment in more detail
...
However,
unemployment is also a potential source of frustration, or “grievances”
...
On the other hand, if violence is driven by the ease of
organizing a violent campaign, unemployment among young men would be particularly important
...
The
two variables are highly correlated (r =
...

Nevertheless, the results are interesting
...
Male youth unemployment, on the other hand,
retains a high, positive coefficient, which is almost significant (t = 1
...
135)
...
What deserves attention is the fact that male youth unemployment completely
dominates overall unemployment
...
It also gives some support to the view that the ethnic
violence was driven by the “greed” of political entrepreneurs rather than the grievances of the
general public
...
Conclusion
As is the case with many conflicts in Africa and elsewhere, the 2007/8 post-election violence
was widely perceived as the result of long-standing ethnic antagonisms (e
...
New York Times 2007)
...
The outbreak of post-election
violence was triggered by the combined effect of ethnic polarization, a flawed election process and
economic forces such as poverty, male youth unemployment and lack of access to public services
...
Therefore, the results indicate that
grievances of the general public and the greed of powerful individuals both contributed to
generating violent conflict in Kenya
...
Future research should investigate whether the insignificant effects of land inequality is
driven by the failure to measure “horizontal inequalities”, that is, inequalities in land ownership
between different ethnic groups (Stewart 2002)
...
The fact that the drivers of ethnic conflict
appear to be economic in nature suggest that perhaps the most effective means to avoiding ethnic
conflict is not to address the issue of ethnicity directly, for example through nation-building policies
or decentralization to local governments of ethnically homogeneous areas (the latter option has
been hotly debated on Kenya under the heading of “majimbo”, or federalism)
...

Africa’s disappointing growth performance is sometimes explained as a result of ethnic
fragmentation (Easterly and Levine 1997)
...


22

References
Anselin, Luc
...
Spatial Econometrics: Methods and Models
...

Barron, Patrick, Kai Kaiser and Menno Pradhan
...
“Understanding Variations in Local Conflict:
Evidence and Implications from Indonesia
...

Blattman, Christopher and Edward Miguel
...
“Civil war
...

Burgess, Robin, Remi Jedwab, Edward Miguel and Ameet Morjaria
...
“Our Turn to Eat: The
Political Economy of roads in Kenya
...

Cheeseman, Nic
...
“The Kenyan Election of 2007: An introduction
...

Collier, Paul and Anke Hoeffler
...
“On Economic Causes of Civil War
...

Collier, Paul and Anke Hoeffler
...
“Greed and Grievance in Civil War
...

Collier, Paul and Anke Hoeffler
...
“Civil War
...
Hartley and T
...
), Handbook of
Defense Economics
...

Deininger, Klaus
...
“Causes and Consequences of Civil Strife: Micro-Level Evidence for Uganda
...

Dercon, Stefan and Roxana Gutierrez-Romero
...
“Triggers and Characteristics of the 2007
Kenyan Electoral Violence
...

Do, Quy-Toan and Lakshmi Iyer
...
“Geography, Poverty and Conflict in Nepal
...

Easterly, William and Ross Levine
...
“Africa’s Growth Tragedy: Policies and Ethnic Divisions
...

Elkins, Caroline
...
“Britain’s Gulag
...
” London: Pimlico
...
and David D
...
1996
...
” American Political
Science Review 90(4): 715-735
...
and David D
...
2003
...
” American Political
Science Review 97(1): 75-90
...
2010
...
” South Asia
Economic Journal 11: 99-110
...
1985
...
” Berkeley: University of California Press
...
2009
...
Journal of Contemporary African Studies 27 (3): 325-344
...
2007
...
” Nairobi: The Government
Printer
...
, and Njuguna S
...
2005
...
): Understanding
Civil War, Vol
...
C
...
, Roxana Gutierrez-Romero
...
“Identity, grievances, and economic
determinants of voting in the 2007 Kenyan elections
...

Kriegler, Johann
...
“Report of the Independent Review Commission on the General Elections held
in Kenya on 27th December, 2007
...

Leo, Christopher
...
“Land and Class in Kenya
...

Mancini, Luca
...
“Horizontal Inequality and Communal Violence: Evidence from Indonesian
Districts
...
22
...
2004
...
”
World Politics 56(3): 327-362
...
2004
...
” Journal of Political Economy 112 (4): 725-753
...
2006
...
” African Affairs 106 (447): 47-70
...
and Marta Reynal-Querol
...
“Ethnic Polarization, Potential Conflict, and Civil
Wars
...

Mueller, Susanne D
...
“The Political Economy of Kenya’s Crisis
...

Neter, John, Michael H
...
Nachtsheim and William Wasserman
...
”Applied
Linear Regression Models
...

New York Times
...
“Tribal Rivalry Boils over after Kenyan Elections”, December 30th
...
2006
...
” Foundation of the Nation
...

Reynal-Querol, Marta
...
“Ethnicity, Political Systems, and Civil Wars
...

Sambanis, Nicholas
...
“Do Ethnic and Nonethnic Civil Wars have the Same Causes?” Journal of
Conflict Resolution 45(3): 259-282
...
2004
...
” Journal of Conflict Resolution 48(6): 814-858
...
2002
...

Waki, Philip N
...
“Report of the Commission of Inquiry into Post Election Violence (CIPEV)
...
2008
...
Volume 1: Synthesis Report
...

Wrong, Michela
...
“It’s Our Turn to Eat
...
” London: Fourth
Estate
...
Dev
...
1
54
...
5
46
...
0
32
...
6
13
...
0
12
...
/sq
...
63
0
...
55
0
...
5
15
...
1
12
...
* Political competition is defined as |votes for Kibaki – votes
for Odinga|/( votes for Kibaki + votes for Odinga)
...
917
(0
...
558)

(0
...
265

0
...
248

-0
...
060)

(0
...
552)

0
...
171

-0
...
080

0
...
261)

(0
...
604)

(0
...
122

-0
...
275

-0
...
318

-0
...
332)

(0
...
207)

(0
...
040)

0
...
244

0
...
335

0
...
083

-0
...
047)

Gini, land

-0
...
414)

Political competition

-0
...
870)

Rural population density

-0
...
072)

Male youth unemployment

0
...
002)

(0
...
383
(0
...
106)

(0
...
025)

(0
...
589)

(0
...
034

0
...
103

-0
...
132

-0
...
195

0
...
818)

(0
...
493)

(0
...
378)

(0
...
190)

(0
...

Only districts with PEV killings, and the districts bordering these districts, are included
...


27

Table 3 Determinants of post-election violence
Kikuyu595
Kikuyu595*poverty rate
Kikuyu595*male youth unemployment
Kikuyu595*change in share with private piped water
Kikuyu595*political competition
Kikuyu595*rural population density
Kikuyu595*land gini
Poverty rate
Male youth unemployment
Change in share with access to private, piped water
Political competition
Rural population density
Gini of agricultural land
Province dummies

Dependent variable: Killings per 100,000 inhabitants
3
...
120*
4
...
244***
(1
...
01)
(3
...
29)
33
...
947***
32
...
187***
(3
...
85)
(4
...
68)
67
...
150***
67
...
776***
(6
...
96)
(7
...
85)
-50
...
072***
-51
...
713***
(5
...
76)
(6
...
58)
-2
...
432
-4
...
52)
(1
...
12)
-0
...
002
(0
...
26)
12
...
77)
-4
...
274
-6
...
922
(0
...
70)
(1
...
68)
4
...
617
4
...
573
(0
...
00)
(1
...
01)
4
...
802
4
...
434
(1
...
01)
(1
...
57)
0
...
507
-0
...
23)
(0
...
39)
0
...
002
(0
...
97)
-0
...
02)
Yes
Yes
Yes
Yes

Observations
44
44
44
44
R-squared
0
...
87
0
...
86
Maximum VIF
8
...
9
5
...
9
OLS regressions
...
Only districts with PEV killings, and the districts bordering
these districts, are included
...
The variables interacted with Kikuyu595
are entered as deviations from means
...
077***
(3
...
411**

2
...
722*

(2
...
28)

(1
...
306

Spatial
regression
4
...
052***

3
...
242

(1
...
11)

(3
...
72)

(1
...
624***

2
...
865*** 25
...
398**

Kikuyu595*male youth unempl
...
707*** 49
...
664*** 35
...
349*** 69
...
307***

(4
...
37)

(3
...
04)

(2
...
301** 30
...
669*** 30
...
06)

(3
...
70)

(2
...
62)

(6
...
71)

(5
...
44)

Kikuyu595*change in share with -47
...
431*** -44
...
151*** -65
...
079*** -51
...
26)
(5
...
73)
(3
...
37)
(7
...
06)
Poverty rate

(3
...
11)

60
...
497*

(7
...
79)

-33
...
530***

(4
...
87)

-4
...
267

-10
...
543*

-6
...
716**

(1
...
17)

(0
...
13)

(2
...
93)

(1
...
27)

4
...
065*

7
...
052

4
...
67

0
...
054

(1
...
79)

(1
...
40)

(1
...
46)

(0
...
07)

-6
...
592
(1
...
172

-7
...
59)

Male youth unemployment

OLS

2
...
911

4
...
223

3
...
704

3
...
079

0
...
62)

(0
...
69)

(0
...
64)

(0
...
92)

(0
...
61)

Yes

Yes

Dependent
variable is
killings
committed by
civilians only

Dependent
variable is
dummy for
more than
10 killings

Lambda

-0
...
19)

Gamma

0
...
15)

Province dummies
Robustness check

Observations
R-squared

Yes

Yes

Yes

Yes

Uasin Gishu Uasin Gishu Nairobi, All districts
excluded and Nakuru Mombasa included
excluded and Kisumu
included

43

42

47

64

0
...
67

0
...
59

Yes
Tobit
model

44

Yes

Yes

Spatial error Spatial lag
model
model

44

44

44

44

0
...
50

Absolute value of t statistics in brackets
...
Nairobi, Mombasa and Kisumu are also excluded, except in regression 3 and 4
...

* significant at 10%; ** significant at 5%; *** significant at 1%

29

Table 5 Determinants of post-election violence - only districts with kikuyu-non-kikuyu polarization
Dependent variable: Killings per 100,000 inhabitants
Poverty rate

15
...
785*

20
...
785*

18
...
151

18
...
31)
Male youth unemployment

17
...
58)

(2
...
64)

(2
...
35)

(0
...
26)

66
...
857*** 66
...
466*** 72
...
311** 56
...
96)

(5
...
20)

(7
...
44)

(3
...
61)

Overall unemployment

80
...
77)
-14
...
14)

Change in share with access
to private, piped water

-41
...
646** -41
...
414*** -47
...
792** -33
...
115*

Gini of agricultural land

(4
...
60)

0
...
017

0
...
49)

(1
...
169

3
...
51)

Political competition

(3
...
16)

Rural population per sq
...


(5
...
86)

(3
...
41)

(2
...
49)

6
...
28)

Rift Valley
Constant

16
...
411*

14
...
221**

8
...
565*

9
...
873

(1
...
23)

(3
...
91)

(2
...
15)

(2
...
61)

-33
...
904** -25
...
626*** -19
...
933** -15
...
215**
(1
...
29)

(4
...
85)

Sample modification

Observations
Adjusted R-squared

(3
...
07)

(2
...
64)

Uasin
Uasin
Nairobi
and
Gishu Gishu and
excluded Nakuru Mombasa
excluded included

11

11

11

11

10

9

13

11

0
...
88

0
...
88

0
...
67

0
...
85

Absolute value of t statistics in brackets
...
Nairobi and Mombasa are excluded, except in regression 7
...
The term “committed by civilians” indicates that killings were not committed by the police
...
/sq
...
) competition land gini
(percent)

Nakuru
263
234
1,602
...
7
41
...
2
Uasin Gishu
230
202
836
...
9
44
...
3
Nairobi
125
102
3,034
...
4
22
...
0
Trans Nzoia
104
27
771
...
6
50
...
2
Kisumu
81
17
620
...
8
43
...
7
Kericho
65
28
630
...
6
42
...
2
Kakamega
31
5
792
...
8
53
...
8
Bungoma
28
14
1,149
...
1
50
...
5
Mombasa
27
23
871
...
3
37
...
8
Migori
26
2
636
...
1
41
...
0
Bureti
24
12
423
...
6
33
...
1
Koibatek
23
16
188
...
2
56
...
1
Narok
19
18
488
...
3
26
...
8
Vihiga
18
3
655
...
8
41
...
6
Butere Mumias
12
1
625
...
8
52
...
3
Siaya
10
1
593
...
1
40
...
2
Bomet
9
7
517
...
6
58
...
3
Kisii
9
5
609
...
1
52
...
9
Busia
9
1
484
...
7
69
...
0
Nandi
7
6
780
...
7
47
...
4
Homa Bay
7
1
359
...
1
42
...
4
Kiambu
4
1
911
...
0
21
...
6
Nyandarua
1
1
587
...
7
49
...
9
Suba
1
1
190
...
1
51
...
3
Baringo
0
0
357
...
2
59
...
2
Bondo
0
0
294
...
1
25
...
8
Gucha
0
0
571
...
1
67
...
9
Kajiado
0
0
545
...
8
12
...
5
Keiyo
0
0
197
...
0
45
...
7
Kilifi
0
0
710
...
7
65
...
5
Kuria
0
0
201
...
1
57
...
2
Kwale
0
0
645
...
1
72
...
4
0
0
432
...
8
48
...
3
Laikipia
Lugari
0
0
281
...
8
48
...
3
Machakos
0
0
1,137
...
2
57
...
1
Maragwa
0
0
473
...
9
31
...
2
Marakwet
0
0
189
...
0
66
...
9
Mt
...
1
1
...
9
8
...
3
95
...
9
13
...
2
0
...
3
4
...
2
0
...
5
9
...
5
96
...
4
3
...
1
0
...
0
7
...
7
0
...
7
9
...
3
88
...
4
25
...
7
11
...
3
4
...
7
2
...
7
0
...


156
179

...

286
436
66
32
1,102
605
375
272
897
403
257
270
655
159
169
39
280
849
21
134
127
312
68
39
396
167
524
118
179
446
656
281
212
392
385
296
77
44

31
...
1
4
...
7
96
...
3
41
...
4
41
...
5
91
...
3
47
...
8
68
...
2
92
...
5
55
...
7
99
...
0
98
...
2
73
...
2
7
...
2
89
...
7
9
...
4
71
...
3
53
...
6
81
...
9
98
...
5
99
...
4
99
...
9
89
...
1
75
...
64
0
...

0
...
47
0
...
55
0
...

0
...
74
0
...
69
0
...
72
0
...
48
0
...
55
0
...
52
0
...
45
0
...
62
0
...
40
0
...
54
0
...
41
0
...
51
0
...
49
0
...
53
0
...
54
0
...
56
0
...
61
0
...
56
0
...
62

10
...
8
17
...
9
1
...
1
-8
...
8
-3
...
5
39
...
2
-18
...
4
-8
...
7
-16
...
7
1
...
8
3
...
8
-9
...
5
8
...
7
-7
...
1
39
...
4
0
...
3
25
...
9
-2
...
6
10
...
8
-1
...
1
1
...
3
0
...
0
5
...
7
4

---