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The Long-Run Eects of the Scramble for Africa
The Long-Run Eects of the Scramble for Africa
Stelios Michalopoulos and Elias Papaioannou
Brown and NBER and CEPR, London Business School and NBER and CEPR
Syracuse University
April 2015
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The Long-Run Eects of the Scramble for Africa
Introduction
Research Question
I Whose country is this ag?
I What does the ve-pointed star symbolize?
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The Long-Run Eects of the Scramble for Africa
Introduction
Research Question
The Scramble for Africa: Consequences for the Somali
Somalis split in:
Somaliland
Ethiopia
Kenya
Somalia
Djibouti
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The Long-Run Eects of the Scramble for Africa
Introduction
Research Question
Questions?. Generalization?
I Has border articiality (w.r.t. ethnic partitioning) contributedto conict in Africa?
I roughly 40% of African population comes from ethnic groups thathave been systematically split across national (colonial) borders
I 220 230 out of 825 ethnic groups were systematically split by
colonial border design (that endured after independence)
I Are there spillovers of ethnic partitioning to nearby groupsand countries (e.g., Ethiopia and Kenya)?
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The Long-Run Eects of the Scramble for Africa
Introduction
Research Question
Examine the Long-run Eects of the Scramble for Africa
I Border articiality (w.r.t. ethnic partitioning)
I
Ethnic partitioning and type of civil conict (battles, violenceagainst civilians, state-driven conict), ethnic political power andaccess to public goods
I using four distinct georeferenced databases
I Further Evidence - Channels
I political discrimination (direct and indirect evidence)
I foreign interventions (direct evidence)
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The Long-Run Eects of the Scramble for Africa
Introduction
Historical Overview
Ethnic Homelands before Colonization - Murdock (1959)
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The Long-Run Eects of the Scramble for Africa
Introduction
Historical Overview
Berlin Conference - The Scramble for Africa
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The Long-Run Eects of the Scramble for Africa
Introduction
Historical Overview
The Design of African Borders
I Berlin Conference 1884/1885 and subsequent treaties among Europeans in
1890s
I Colonizers had not even explored most of Africa when borders were agreed.
I Drawing involved protectorates, large (free-trade) areas, colonies, and
spheres of inuence rather than potential states. None could foresee at thetime independence
I No major changes of borders during colonization or after independence
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The Long-Run Eects of the Scramble for Africa
Introduction
Historical Overview
Current National Boundaries and Ethnic Homelands
At independence borders
were respected creating
boundaries of African states
Th L R E f h S bl f Af i
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The Long-Run Eects of the Scramble for Africa
Introduction
Historical Overview
A European Randomization...
I "we have been engaged in drawing lines upon maps where no whitemans feet have ever tord; we have been giving away mountains and
rivers and lakes to each other, only hindered by the smallimpediment that we never knew exactly where the mountains and
rivers and lakes were." Lord Salisbury (British PM)
I "the study of European archives supports the accidental rather thana conspiratorial theory of the marking of African boundaries."Asiwaju
(1985)
Th L R E t f th S bl f Af i
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The Long-Run Eects of the Scramble for Africa
Introduction
Historical Overview
Partitioning of Tribal Areas - Binary Classication
Ethnic Homelands
and National Borders
National Boundaries
Non-Partitioned Groups
Partitioned Groups
The Long R n Eects of the Scramble for Africa
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The Long-Run Eects of the Scramble for Africa
Introduction
Historical Overview
Population Belonging to Partitioned Ethnicities
.2
.4
.6
.8
1
Density
0 .5 1% of a Country's Population Belonging to Partitioned Ethnicities in 2000
kernel = epanechnikov, bandwidth = 0.1332
Kernel density estimate
The Long Run Eects of the Scramble for Africa
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The Long-Run Eects of the Scramble for Africa
Introduction
Literature
Deep Determinants of African Development
1. Importance of National Contemporary Institutions(Acemoglu et al. (2001, 2002, 2005); La Porta et al. (1998, 1999); Glaeser et al.
(2004); Michalopoulos and Papaioannou (2014))
I Colonization (type or/and identity)
2. Pre-colonial Institutions, Slavery, and Other Ethnic Traits(Herbst (2000); Gennaioli and Rainer (2006, 2007); Michalopoulos and Papaioannou
(2013), Nunn (2008), Nunn and Wantchekon (2011), Fenske (2014))
I Limited penetration of nationwide institutions (poor infrastructure,peculiar country shapes, Michalopoulos and Papaioannou (2014))
I Colonization limited (in duration and location)
I Weak state capacity (Migdal 1988, Besley and Persson, 2010)
The Long-Run Eects of the Scramble for Africa
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The Long-Run Eects of the Scramble for Africa
Introduction
Literature
This Paper
..focuses on the long-run eects of the Scramble for Africa
I African historiography (e.g., Dowden (2008); Englebert (2010))
I so far have been neglected in economics
I Border Design - State Articiality(Englebert, Tarrango, and Carter (2002); Alesina, Easterly, and Matuszeski (2011))
The Long-Run Eects of the Scramble for Africa
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The Long Run Eects of the Scramble for Africa
Introduction
Literature
This Paper
..focuses on the long-run eects of the Scramble for Africa
I African historiography (e.g., Dowden (2008); Englebert (2010))
I so far have been neglected in economics
I Border Design - State Articiality(Englebert, Tarrango, and Carter (2002); Alesina, Easterly, and Matuszeski (2011))
The Long-Run Eects of the Scramble for Africa
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o g o S o
Introduction
Literature
Related Works
I Ethnic Fragmentation/Polarization and Conict/Development(e.g., Easterly and Levine (1997), Alesina et al. (2003), Fearon ( 2003), Collier and
Hoeer (2007), Montalvo and Reynal-Querol (2005a,b), Esteban, Ray, and Mayoral
(2012), Esteban and Ray (2007, 2011), Alesina, Michalopoulos, and Papaioannou
(2015a,b))
I Origins of Civil War and Conict (e.g., Herge and Sambanis (2006); Kalyvas(2007); reviews Blattman and Miguel (2010) and Collier and Sambanis (2005))
I Civil Conict in Africa - Geo-referenced Data (Harari and La Ferrara(2014); Besley and Reynal-Querol (2014); Berman et al. (2014))
I Long-run consequences of historical events (e.g., Guiso et al. 2008; Huillery,2009; Banerjee and Iyer, 2005; Iyer, 2010; Dell, 2011; Acemoglu et al. 2008; Jedwab
and Moradi, 2012; reviews Nunn (2015) and Fuchs-SchundelnandHassan(2015))
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g
Introduction
Literature
Our Study: Shift the Agenda to the Scramble for Africa
I Exploiting as a quasi-natural experiment the random drawing of political
boundaries during the Scramble for Africa
I African historiography extensively argues that the borders were randomly drawn
(at least w.r.t. to the groups on the ground)
I Establish border arbitrariness (useful for future research)
I Exploiting regional variation (straightforward econometric benets)
I Unobserved country characteristics (colonization, national policies, state capacity)
I Information at the time of colonization (before independence)
I Control for local factors (e.g., natural resources, malaria)
I Studying the eect of partitioning on conict
I This has been hypothesized to be the main channel.
I Important from policy standpoint (autonomy, regionalism).
I Analysis of mechanisms (state-driven conict, interventions fromnearbycountries)
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Introduction
Mechanisms
Channels Linking Partitioning to Civil War
I Unlike non-split groups, partitioned ethnicities have the advantage of
getting assistance from their peers on the other side of the border as well
and nd a safe heaven when in need to retreat and regroup.
I Somali tribes in Ethiopia
I Neighboring governments exploit the presence of co-ethnics across the
border to intervene to stage interventions.
I Casamance region in Southern Senegal, where the partitioned ethnic groups Diola
and the Banyun reside
I Partitioned groups are discriminated and often excluded from the political
sphere. Partitioned ethnicities react to their marginalization by
participating in coups, rebellions against the government.
I Ewe in Ghana; Alur in DRC.
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Introduction
Mechanisms
Channels Linking Partitioning to Civil War (cont.)
I Irredentist demands, as ethnicities that are minority groups in a country
want to unify with their peers across the border
I 3 civil wars in the homeland of the Somalis partitioned between Somalia, Djibouti,
Kenya, Ethiopia
I Partitioned ethnicities ght to secede or obtain more autonomy
I Diolas in the Casamance region in Southern Senegal
I Border disputes due to the poor demarcation of borders particularly in caseof partitioned groups
I ambiguity of the tripartite treaty between Britain, Italy and Ethiopia of 1902 has
also played a role in the Eritrea-Ethiopia devastating war
The Long-Run Eects of the Scramble for Africa
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Introduction
Mechanisms
Consequences of the Scramble Besides Partitioning
I African border design determined all country-wideaspects related to
I geography, i.e., landlocked, country size, ruggedness, shape, diseaseenvironment etc.
I societal structure, i.e., ethnic fractionalization, polarization,inequality, etc.
I Do not quantify their inuence on conict but account for their
importance with the inclusion of country xed eects.
I Explore how these dierent nationwide by-products of the Scramble for
Africa interact with ethnic partitioning in shaping local conict (tentative).
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Introduction
Roadmap
Presentation Structure
I Border Articiality (split vs. non-split)
I Ethnic Partitioning and Civil Conict (ACLED)
I baseline estimatesI
conict types (battles, violence against civilians, riots) and conictactors (government, rebels-militias, external)I sensitivity analysisI further evidence with alternative conict data (UCDP-GED)
I Ethnic Partitioning and Political Representation (EPR)
I Political Discrimination and Ethnic Wars
I Ethnic Partitioning and Public Goods (DHS)
I Identity and Location (further look at discrimination)
I Summary-Conclusion
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Border Articiality
Objective
I African historiographers argue that Europeans did not take intoaccount local (geographic, political) conditions when delineatingborders
I
Yet in some cases they didI some (few) border realignments
I Approach 1: Balancedness Tests ("similarity regression tests")
I compare split and non-split ethnic homelands across many observable
features (tests of means, medians, distribution)
I Approach 2: Examine whether some specic observablefeatures correlate with ethnic partitioning
I similar to approach 1, but more intuitive given the nature of the
experiment
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Border Articiality
Empirical Specication
Empirical Specication
SPLITi =a+GEOi+HISTi+PRECOLONIALi+ar+"i
I SPLITi : indicator whether the historical homeland of ethnic group iis partitioned by national boundaries
I 10% thresholdI Other thresholds (and continuous measures)
I GEOi : vector of geographic variables (at the ethnicity level).
I HISTi : vector of historical characteristics (at the ethnicity level).
I PRECOLONIALi : pre-colonial ethnic-specic traits.
I ar : region xed eects (North, South, Central, East, West Africa)
The Long-Run Eects of the Scramble for Africa
B d A i i li
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Border Articiality
Results
Border Articiality I. Geography(1) (2) (3) (4) (5)
Log Land Area 0.05 56 ** * 0.05 29 ** * 0.06 18 ** * 0.05 54 ** * 0.04 89 ** *(0.0 15 3) (0.0 15 9) (0.0 175 ) (0.01 86 ) (0.01 50 )
Lake Indicator 0.0961* 0.0963 0.0965* 0.0971*(0.0 56 5) (0.0 645 ) (0.05 67 ) (0.05 58 )
River Indicator -0.0053 -0.0164 -0.0092 -0.0065
(0.0 33 7) (0.0 324 ) (0.03 25 ) (0.03 38 )
Elevation -0.0411(0.0709)
Suitability for Agriculture 0.1239(0.0974)
Malaria Stability Index 0.0195
(0.0982)
Distance to the Coast 0.0000(0.0001)
Diamond Mine Indicator 0.0359(0.0651)
Oil Indicator 0.0285
(0.0565)
-
The Long-Run Eects of the Scramble for Africa
B d A ti i lit
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Border Articiality
Results
Border Articiality II. Pre-colonial History(1) (3) (3) (4) (5) (6) (7)
Pre-colonial Conict Indicator -0.0663(0.0733)
Distance to Pre-colonial Conict -0.0444(0.0839)
Slave Trades Indicator 0.0045
(0.0322)
Log Number of Slaves 0.0063(normalized by land area) (0.0080)
Pre-colonial Kingdom Indicator 0.0466(0.0469)
Distance to Pre-colonial Kingdom 0.0009
(0.1235)
Major City in 1400AD 0.0233(0.0652)
Adjusted R-square 0.056 0.056 0.055 0.056 0.057 0.055 0.055Size, River and Lake Indicators Yes Yes Yes Yes Yes Yes YesRegion Fixed Eects Yes Yes Yes Yes Yes Yes Yes
Observations 825 825 825 825 825 825 825
The Long-Run Eects of the Scramble for Africa
Border Articialit
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Border Articiality
Results
Border Articiality III. Pre-colonial Ethnic Traits
(1) (2) (3) (4) (5) (6) (7)
Complex Settlement Patterns -0.0004(0.0538)
Share of Agriculture 0.0015(0.0112)
Animal Husbandry (0.0088)(0.0108)
Elections -0.0459(0.0848)
Inheritance Rule for Property 0.0040(0.0891)
Political Centralization -0.0719(0.0482)
Class Stratication -0.0674(0.0444)
adjusted R-squared 0.081 0.081 0.082 0.095 0.0790 0.0830 0.098Size, River and Lake Indicators Yes Yes Yes Yes Yes Yes YesRegion Fixed Eects Yes Yes Yes Yes Yes Yes YesObservations 451 451 437 437 394 394 487
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Border Articiality
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Border Articiality
Results
Results Summary: Border Articiality
I among numerous geographic, ecological, and local conditions variables only
land area and area under water (lakes) correlate with partitioning
I out of various pre-colonial ethnic-specic institutional, cultural, economic,
and social variables (reported in George Peter Murdocks Ethnolinguistic
Atlas), none correlates with border drawing
I these simple results (though do not prove by themselves the random border
design) consistent with the vast literature on ethnic partitioning during the
Scramble for Africa arguing that Europeans paid little attention to local
conditions when drawing political boundaries (Asiwaju, 1985)
I at the time no prospect of independenceI implicit understanding that people could move across borders
The Long-Run Eects of the Scramble for Africa
Border Articiality
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Border Articiality
Results
Further Evidence: Balancedness Tests
I Estimate "similarity regressions" (with country xed eects)associating various geographic, location, natural resource andecology variables with the ethnic partitioning index.
I full sample (1212 country-ethnic homelands)
I border sample (606 country-ethnic homelands)
I No major (within country) dierences in observable characteristics
between split and non-split ethnic homelands
I unobservable features should be way more important than observables(Altonji et al. (2004), Oster (2014))
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Border Articiality
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Border Articiality
Results
Similarity Regressions
Log Land
Area
Lake
Indicator
River
Indicator
Mean
Elevation
Land
Suitability
Malaria
Stability
Diamond
Indicator
Petroleum
Indicator
Major City
in 1400
Coastal
Indicator
Capital
Indicator
Distance
Sea
Distance
Border
Distance
Capital
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)
SPLIT -0.1702 -0.0027 0.0023 0.0165 0.0009 -0.0092 -0.0132 -0.0212 -0.0005 -0.0173 -0.024 0.0219 100.8410**0.1059***(0.1045) (0.0225) (0.0333) (0.0365) (0.0193) (0.0218) (0.0189) (0.0220) (0.0094) (0.0274) (0.0159) (0.0316) (13.3237) (0.0276)
marginal R2 0.003 0.000 0.000 0.001 0.000 0.000 0.001 0.001 0.000 0.001 0.003 0.000 0.154 0.017
Mean Dep. Var 2.071 0.108 0.504 0.617 0.407 0.717 0.093 0.084 0.026 0.129 0.039 0.600 107.412 0.505
Observations 1212 1212 1212 1212 1212 1212 1212 1212 1212 1212 1212 1212 1212 1212
Country FE Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
SPLIT 0.7236*** -0.0191 0.0864* 0.0010 0.0243 -0.0090 0.0123 0.0095 0.0057 0.0475 0.0118 -0.0268 -1.9752 -0.0128
(0.1762) (0.0294) (0.0399) (0.0326) (0.0154) (0.0214) (0.0250) (0.0212) (0.0045) (0.0311) (0.0094) (0.0303) (2.8585) (0.0370)
marginal R2 0.052 0.001 0.005 0.000 0.002 0.000 0.001 0.001 0.002 0.005 0.001 0.001 0.002 0.000
Mean Dep. Var 1.2276 0.0941 0.4620 0.5928 0.4314 0.7714 0.0594 0.0413 0.0033 0.1089 0.0215 0.5855 24.8881 0.5163
Observations 606 606 606 606 606 606 606 606 606 606 606 606 606 606
Country FE Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Dependent variable is:
Panel A: All Country-Ethnic Homelands
Panel B: Country-Ethnic Homelands close to the National Border
The Long-Run Eects of the Scramble for Africa
Border Articiality
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o de t c a ty
Results
Border Articiality. A Caveat
I almost impossible to establish randomization BUT
I empirical results in line with African historiography on the limited (atbest) knowledge of colonizers at the time
I It has to be that the factors that somehow aected partitioning atthe time when no-one could foresee independence matter crucially
for contemporary conict (quite unlikely)
The Long-Run Eects of the Scramble for Africa
Conict Data; Patterns
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;
Types of Conict
Main Dataset
I Source: Armed Conict Location and Events Dataset,ACLED. (vintage 4)
I Raleigh, Linke, Hegre, and Karlsen (2010); Raleigh, Linke, and Down(2014)
I Period: 1997 2013
I Sample: All African countries (but some small islands)
I Original Sources: Reuters, BBC, Associated Press, Agence FrancePress, United Nations Reports, NGOs, etc.
The Long-Run Eects of the Scramble for Africa
Conict Data; Patterns
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Types of Conict
Classication. 4 Categories
I Battles, mostly between government forces, rebels, and militias.(23; 381 events, 9; 596 deadly).
I Violence against civilians, by militias (40%), government troops(25%) and rebels (25%). (20; 409 events, 8; 777 deadly).
I Riots and protests. mostly in capitals. (16; 147 events, 1; 040
deadly).I Non-violent activities by conict actors. (4; 727 events, 42 deadly).
The Long-Run Eects of the Scramble for Africa
Conict Data; Patterns
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Types of Conict
Civil Conict. ACLED 1997-2013
Type of Violent
Events in ACLED
African Boundaries
Battle
Non-violent activity
Riots/Protests
Violence against civilians
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Conict Data; Patterns
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Types of Conict
Conict Examples
I Battles:I September 1999 the Ugandan army killed 42 Pian warriors, coming from the
Karamojong group split between Uganda, Sudan, and Kenya;
I August 1997 government forces of the Congo DRC retook control of the town of
Watsa, close to the border with Uganda, where the partitioned Alur reside. 800
casualties;
I Violence Against Civilians:
I raids of the Janjaweed militias against civilian population in the Darfur region;
I the assaults and tortures by Presidents Mugabes Central Intelligence
Organization in Zimbabwe;I burning of churches, hostage-taking and child-soldiering raids by rebels in Nigeria
and in Sierra Leone
I Riots and Protests
I Arab Spring
I Marikana events in South Africa
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Conict Data; Patterns
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Types of Conict
Classication. 8 Conict Actors
I Government Forces
I Rebel Forces (political organizations whose goal is to counter an established nationalgoverning regime by violent acts)
I Ethnic and Political Militias (created for a specic purpose or during a specictime period; oering protection/policing, involved in communal violence, etc.)
I Rioters
I Protesters
I Civilians
I Outside/external forces
I intervention by nearby countriesI peace-keeping (UN, African Union)and outside military involvement
(NATO, France)
The Long-Run Eects of the Scramble for Africa
Conict Data; Patterns
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Types of Conict
Conict Events by Actor
Actors
African Boundaries
Government Forces
Rebel Forces
Political Militias
Ethnic Militias
Rioters
Protesters
Civilians
External Forces
The Long-Run Eects of the Scramble for Africa
Specication
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Unit of Analysis: Country-Ethnic Homelands
Conict across Country-Ethnic Homelands
Violent Events Across
Ethnic Homelands 97-13
African Boundaries
ACLED: Violent Events
0
1 - 2
3 - 6
7 - 13
14 - 31
32 - 89
90 - 5423
Fatal Violent Events in
Ethnic Homelands 97-13
African Boundaries
ACLED: Fatal Violent Events
0
1
2 - 3
4 - 7
8 - 15
16 - 35
36 - 2299
The Long-Run Eects of the Scramble for Africa
Specication
E i i
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Estimation
Empirical Specication
yi;c =a+SPLITi+SPILi;c+X0
i;c +ac+"i;c
I yi;c : civil conict at the homeland of ethnicity i in country c.
I SPLITi;c : Binary ethnic partitioning index. [518 partitioned, 694 non-split]
I SPILi;c : Share of adjacent split groups (spillovers). [mean 0.41]
I Xi;c : vector of control variables (at the country-ethnicity level).
I including distance to the national borderI including log land area, water indicators, and log population at
independence (simple controls)
I ac : country xed eects [national politics, type of colonization, state capacity,
ethnic composition, etc.]
The Long-Run Eects of the Scramble for Africa
Specication
E ti ti
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Estimation
Empirical Specication, cont.
I to minimize concerns that the partitioning indicator is capturing anoverall border eect, we also restrict estimation to ethnic areas nearthe national border
yi;c =a+SPLITi+SPILi;c+X0
i;c +ac+"i;c
if BDISTi;
c
-
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Estimation
Rich Set of Control Variables at a Fine Grid
I suitability for agriculture, elevation
I natural resources (diamond mines, oil/petroleum elds)
I malaria stability index (from Columbias Earth Institute)
I distance to border (and higher order polynomial terms)
I distance to the sea coast
I distance to the capital city
I capital city indicator
I coastal indicator
I more
The Long-Run Eects of the Scramble for Africa
Specication
Estimation
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Estimation
Technical Issues
I Count data
I Signicant fraction of the observations on regional civil war takes onthe value of zero (25%).
I Some extreme observations in the right tail of the distribution (e.g.,all conict events mean=53:4; p50= 4; p99= 102; max=5; 423)
Approach
I
Negative Binomial ML estimation with country constantsI Linear Probability Model (LPM) estimates (extensive margin)
I Poisson ML model estimation dropping outliers (top 5%, top 10%)
I Conditional Negative Binomial ML estimation (Hahn, Hausman, andGriliches, 1984)
The Long-Run Eects of the Scramble for Africa
Specication
Estimation
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Estimation
Alternative Aspects of Civil Conict
I Deadly conict incidents
I NB-ML with country constants
I LPM (OLS) with country xed eects
I Conditional NB modelsI Country xed-eects Poisson (no outliers)
I Fatalities (NB-ML with country constants)
I Duration in years (NB-ML and Poisson-ML with countryxed-eects)
I all incidents
I deadly incidents
The Long-Run Eects of the Scramble for Africa
Specication
Estimation
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Estimation
Inference
I "Standard" heteroskedasticity-adjusted standard errors unreliable.
I Report double clustered s.e. with clustering at the country-level and
at the ethnic family level (Cameron, Gelbach, and Miller (2011))
1. Account for (i) within country correlation; (ii) correlation of ethniccultural, political, economic traits within ethnic families.
2. Account for spatial correlation.
I Conleys (1999) method yields similar (and if anything somewhatsmaller) standard errors.
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Results Preview
I Preliminary Evidence
I Tests of Means and Medians (Full Sample and Border Sample)
I Regression Analysis (Full Sample and Border Sample)
I Conict Events (number and likelihood)I Intensity (Duration, Fatalities, Deadly Events)I Type of Conict (battles, civilian violence, riots-protests)I Sensitivity Analysis
I Digging Deeper.
I Conict Actor (government troops, rebels, militias, foreigninterventions)
I Further evidence of actor-based analysis
I Taking Stock
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y
Tests of Means and Medians. All Events
Indicator
Likelihood
mean mean median mean median mean median
(1) (2) (3) (4) (5) (6) (7)
non-partitioned ethnic groups (N=596) 0.815 47.616 3.000 30.495 3.000 30.464 3.000
partitioned ethnic groups (N=229) 0.878 65.031 13.000 47.872 10.000 52.526 13.000
difference 0.062 17.415 10.000 17.377 7.000 22.062 10.000
difference (p-value) (0.07) (0.42) (0.00) (0.05) (0.09) (0.02) (0.01)
non-partitioned ethnic groups (N=200) 0.873 32.300 1.000 29.270 1.000 24.704 1.000
partitioned ethnic groups (N=213) 0.725 66.067 12.000 47.249 10.000 52.524 12.000
difference 0.148 33.667 11.000 17.978 9.000 27.820 11.000
difference (p-value) (0.00) (0.10) (0.01) (0.09) (0.02) (0.00) (0.00)
Panel A: All Ethnic Homelands
Panel B: Ethnic Homelands close to the National Border
Number of
Incidents - All
Excluding
Capitals
Excluding
Outliers (top 1%)
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Tests of Means and Medians. Battles
Indicator
Likelihood
mean mean median mean median mean median
(1) (2) (3) (4) (5) (6) (7)
non-partitioned ethnic groups (N=596) 0.649 19.837 1.000 14.551 1.000 12.566 1.000
partitioned ethnic groups (N=229) 0.725 30.052 3.000 22.782 2.000 21.212 2.000
difference 0.076 10.215 2.000 8.231 1.000 8.646 1.000
difference (p-value) (0.33) (0.20) (0.03) (0.10) (0.19) (0.03) (0.12)
non-partitioned ethnic groups (N=200) 0.550 15.700 0.000 13.867 0.000 9.879 0.000
partitioned ethnic groups (N=213) 0.714 30.230 3.000 22.173 2.000 20.719 3.000
difference 0.164 14.530 3.000 8.305 2.000 10.840 3.000
difference (p-value) (0.00) (0.16) (0.15) (0.18) (0.10) (0.01) (0.01)
Number of
Incidents - All
Excluding
Capitals
Excluding
Outliers (top 1%)
Panel A: All Ethnic Homelands
Panel B: Ethnic Homelands close to the National Border
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Tests of Means and Medians. Civilian Violence
Indicator
Likelihood
mean mean median mean median mean median
(1) (2) (3) (4) (5) (6) (7)
non-partitioned ethnic groups (N=596) 0.683 17.648 1.000 10.502 1.000 10.007 1.000
partitioned ethnic groups (N=229) 0.777 23.258 3.000 16.758 2.000 17.079 3.000
difference 0.094 5.610 2.000 6.257 1.000 7.073 2.000
difference (p-value) (0.05) (0.53) (0.03) (0.05) (0.10) (0.05) (0.03)
non-partitioned ethnic groups (N=200) 0.615 11.390 0.000 10.786 0.000 7.525 0.000
partitioned ethnic groups (N=213) 0.765 24.033 3.000 16.919 2.000 17.393 3.000
difference 0.150 12.643 3.000 6.133 2.000 9.868 3.000
difference (p-value) (0.00) (0.13) (0.01) (0.08) (0.00) (0.00) (0.00)
Number of
Incidents - All
Excluding
Capitals
Excluding
Outliers (top 1%)
Panel A: All Ethnic Homelands
Panel B: Ethnic Homelands close to the National Border
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Ethnic Partitioning and Civil Conict. NB-ML Estimates.
Full Sample
All Observations Excl. Out. Excl. Cap.(1) (2) (3) (4) (5) (6)
SPLIT (Partitioning) 0.4513*** 0.3329** 0.4495*** 0.4626*** 0.4494*** 0.4565***
Double-clustered s.e. (0.1611) (0.1851) (0.1254) (0.1201) (0.1172) (0.1236)
SPIL (Adjacent Split) 0.0481 0.391 0.4619* 0.4920* 0.4834* 0.4256*Double-clustered s.e. (0.2789) (0.3430) (0.2626) (0.2628) (0.2686) (0.2760)
Log Likeliho od -4506.794 -4280.17 -4119.95 -4108.72 -3993.15 -3781.29Observations 1212 1212 1212 1212 1199 1165
Simple Controls Yes Yes Yes Yes Yes YesLocation Controls No No Yes Yes Yes YesGeographic Controls No No No Yes Yes YesCountry Fixed Eects No Yes Yes Yes Yes Yes
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Ethnic Partitioning and Civil Conict. NB ML Estimates.
Close to the National Border
All Observations Excl. Out. Excl. Cap.(1) (2) (3) (4) (5) (6)
SPLIT (Partitioning) 0.9247*** 0.8050*** 0.6014*** 0.5906*** 0.5906*** 0.5806***Double-clustered s.e. (0.1704) (0.2372) (0.2226) (0.2176) (0.2176) (0.2146)
SPIL (Adjacent Split) 0.0879 0.5679 0.4328 0.4514 0.4514 0.3928Double-clustered s.e. (0.5748) (0.4733) (0.3818) (0.3565) (0.3565) (0.3640)
Log Likeliho od -1697.469 -1561.61 -1518 -1510.73 -1510.733 -1445.62Observations 579 579 579 579 579 568
Simple Controls Yes Yes Yes Yes Yes YesLocation Controls No No Yes Yes Yes YesGeographic Controls No No No Yes Yes YesCountry Fixed Eects No Yes Yes Yes Yes Yes
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Ethnic Partitioning and Civil Conict. LPM Estimates.
Full Sample
All Observations Excl. Out. Excl. Cap.(1) (2) (3) (4) (5) (6)
SPLIT (Partitioning) 0.0562** 0.0660*** 0.0783*** 0.0819*** 0.0839*** 0.0789***
Double-clustered s.e. (0.0241) (0.0238) (0.0258) (0.0266) (0.0266) (0.0266)
SPIL (Adjacent Split) 0.0571 0.1146*** 0.1284*** 0.1443*** 0.1487*** 0.1468***Double-clustered s.e. (0.0486) (0.0394) (0.0397) (0.0408) (0.0402) (0.0408)
Log Likelihood 0.304 0.43 0.44 0.445 0.446 0.446Observations 1212 1212 1212 1212 1199 1162
Simple Controls Yes Yes Yes Yes Yes YesLocation Controls No No Yes Yes Yes YesGeographic Controls No No No Yes Yes YesCountry Fixed Eects No Yes Yes Yes Yes Yes
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Ethnic Partitioning and Civil Conict. LPM Estimates.
Close to the National Border
All Observations Excl. Out. Excl. Cap.(1) (2) (3) (4) (5) (6)
SPLIT (Partitioning) 0.0874** 0.0835* 0.0821 0.0903** 0.0903** 0.0893*Double-clustered s.e. (0.0399) (0.0484) (0.0523) (0.0457) (0.0457) (0.0461)
SPIL (Adjacent Split) 0.1787*** 0.2246*** 0.2297*** 0.2444*** 0.2444*** 0.2347***Double-clustered s.e. (0.0594) (0.0604) (0.0631) (0.0562) (0.0562) (0.0575)
Log Likelihood 0.315 0.463 0.475 0.489 0.489 0.486
Observations 579 579 579 579 579 568
Simple Controls Yes Yes Yes Yes Yes YesLocation Controls No No Yes Yes Yes YesGeographic Controls No No No Yes Yes YesCountry Fixed Eects No Yes Yes Yes Yes Yes
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Ethnic Partitioning and Civil Conict Intensity. Full Sample
Deadly Incidents Deadly Indicator Casualties Dur. All Dur. DeadlyNB-ML LPM NB-ML Poisson Poisson
(1) (2) (3) (4) (5)
SPLIT (Partitioning) 0.3356** 0.0599** 0.4843*** 0.2015*** 0.1658**
Double-clustered s.e. (0.1357) (0.0287) (0.1651) (0.0622) (0.0740)
SPIL (Adjacent Split) 0.3948 0.1461*** 0.1161 0.2478** 0.3648**Double-clustered s.e. (0.2465) (0.0463) (0.3121) (0.1174) (0.1629)
Log Likelihood -2910.906 -4516.44 -2759.21 -2232.74adjusted R-square 0.411
Simple Controls Yes Yes Yes Yes YesLocation Controls Yes No Yes Yes YesGeographic Controls Yes No No Yes YesCountry Fixed Eects Yes Yes Yes Yes YesObservations 1212 1212 1199 1212 1212
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Ethnic Partitioning and Civil Conict Intensity. Close to
the National Border
Deadly Incidents Deadly Indicator Casualties Dur. All Dur. DeadlyNB-ML LPM NB-ML Poisson Poisson
(1) (2) (3) (4) (5)
SPLIT (Partitioning) 0.4651** 0.0820* 0.8489*** 0.2784** 0.4350***Double-clustered s.e. (0.2037) (0.0428) (0.3787) (0.1216) (0.1521)
SPIL (Adjacent Split) 0.2745 0.2378*** 0.3573 0.3731** 0.4674*Double-clustered s.e. (0.3110) (0.0611) (0.5155) (0.1804) (0.2415)
Log Likelihood -1028.821 -1657.27 -1057.16 -805.15adjusted R-square 0.449
Simple Controls Yes Yes Yes Yes YesLocation Controls Yes Yes Yes Yes YesGeographic Controls Yes Yes Yes Yes YesCountry Fixed Eects Yes Yes Yes Yes Yes
Observations 579 579 575 579 579
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Ethnic Partitioning and Main Civil Conict Categories. Full
SampleBattles Civilian Violence Riots - Protests
NB-ML LPM NB-ML LPM NB-ML LPM(1) (2) (3) (4) (5) (6)
SPLIT (Partitioning) 0.4428*** 0.0912** 0.4328*** 0.0517 0.0747 0.0193Double-clustered s.e. (0.1489) (0.0375) (0.1229) (0.0320) (0.1526) (0.0305)
SPIL (Adjacent Split) 0.4846 0.0631 0.3816 0.1749*** 0.4119 0.0773Double-clustered s.e. (0.3060) (0.0442) (0.3523) (0.0577) (0.2574) (0.0533)
Log Likelihood -2918.506 -2876.56 -2203.732
Observations 0.465 0.422 0.439
Simple Controls Yes Yes Yes Yes Yes YesLocation Controls Yes Yes Yes Yes Yes YesGeographic Controls Yes Yes Yes Yes Yes YesCountry Fixed Eects Yes Yes Yes Yes Yes YesObservations 1212 1212 1212 1212 1212 1212
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Summary Economic Magntitudes
I Number of Events (intensity): approx. 60% 70%(mean 53 events)
I Deadly Events: approx. 50% 70% (mean 16 events)
I Conict Likelihood: 5% 8: 5% (mean 73%)
I Duration: 25% (mean 4 5 years, median 2:5 years)
I
Duration Deadly: 30%
40% (mean 2:7 years, median 1 year)I Casualties: 100% 180% (mean 317 deaths)
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Digging Deeper
I Ethnic-based discrimination, suocation from government andopposition [rebels, militias]
I Interventions from nearby countries [shelter, regrouping]; "proxy"wars ["internationalized internal" civil wars, PRIO]
I In contrast, no arguments linking partitioning with riots and
protests; mostly urban phenomena (capitals and big cities)
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State Conict (Government Forces, Rebels and Militias)
Actors Involved
in Violence
African Boundaries
Government
Actors Involved
in Violence
African Boundaries
Rebels
Actors Involved
in Violence
African Boundaries
Militias
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Violence against Civilians and Riots-Protests
Actors Involved
in Violence
African Boundaries
Civilians
Actors Involved
in Violence
African Boundaries
Riots and Protests
Actors Involved
in Violence
African Boundaries
Neighboring Governments
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Neighboring Countries Interventions. Examples
I 18/4/1997: "Sudanese government military repulsed an attack by
Ugandan military which began with 4 days of shelling the area -more than
300 Ugandan soldiers were reportedly killed." (Madi homeland in Sudan)
I
4/12/2013 "Ethiopian forces kill a civilian man in Somalia and a memberof the local government administration after he criticized their presence in
Somalia. Two other civilians were injured." (Shebelle homeland in
Somalia).
I
05/07/2007: "Sudan occupies territory of Alur in the Democratic Republicof Congo for administrative reasons." (Lugbara homeland in DRC)
I 26/5/2001: "Guinean military attacks Liberian army in support of Liberian
dissidents" - (Toma homeland in Liberia)
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Ethnic Partitioning and Main Civil Conict Actors. Full
Sample
All Homelands Homelands close to the BorderGovernm. Reb.-Mil. Neighbor External Governm. Reb.-Mil. Neighbor External
(1) (2) (3) (4) (5) (6) (7) (8)
SPLIT (Partitioning) 0.5247*** 0.4908*** 1.1280*** 0.244 0.1089*** 0.0663** 0.0658** 0.0065Double-clustered s.e. (0 .13 94 ) (0 .13 81 ) (0 .25 77 ) (0.2 53 4) (0.0 28 1) (0.0 32 7) (0.0 32 5) (0.0 228 )
SPIL (Adjacent Split) 0.496 0.3258 0.1629 -0.519 0.1300** 0.1059** 0.0737 -0.009Double-clustered s.e. (0 .31 08 ) (0 .30 89 ) (0 .43 27 ) (0.4 76 5) (0.0 53 0) (0.0 48 2) (0.0 46 6) (0.0 292 )
Log Likelihood -3213.3 -3538.276 -1088.254 -571.588 0.453 0.472 0.345 0.378Observations 1212 1212 1178 682 1212 1212 1212 1212
Simple Controls Yes Yes Yes Yes Yes Yes Yes YesLocation Controls Yes Yes Yes Yes Yes Yes Yes YesGeographic Controls Yes Yes Yes Yes Yes Yes Yes YesCountry Fixed Eects Yes Yes Yes Yes Yes Yes Yes YesObservations 1212 1212 1178 682 1212 1212 1212 1212
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Ethnic Partitioning and Main Civil Conict Actors. Full
Sample
All Homelands Homelands close to the BorderGovernm. Reb.-Mil. Neighbor External Governm. Reb.-Mil. Neighbor External
(1) (2) (3) (4) (5) (6) (7) (8)
SPLIT (Partitioning) 0.1089*** 0.0663** 0.0658** 0.0065 0.1240*** 0.0861* 0.0693** 0.0349Double-clustered s.e. (0.0281) (0.0327) (0.0325) (0.0228) (0.0426) (0.0497) (0.0342) (0.0298)
SPIL (Adjacent Split) 0.1 30 0* * 0.1 05 9* * 0.07 37 -0 .0 09 0.1 90 5** * 0 .1 671 ** * 0.0 07 4 -0.0 62 5Double-clustered s.e. (0.0530) (0.0482) (0.0466) (0.0292) (0.0625) (0.0619) (0.0487) (0.0415)
Log Likelihood 0.453 0.472 0.345 0.378 0.467 0.485 0.384 0.425Observations 1212 1212 1212 1212 579 579 579 579
Simple Controls Yes Yes Yes Yes Yes Yes Yes YesLocation Controls Yes Yes Yes Yes Yes Yes Yes YesGeographic Controls Yes Yes Yes Yes Yes Yes Yes YesCountry Fixed Eects Yes Yes Yes Yes Yes Yes Yes Yes
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A Closer Look
I Results (so far):
I ethnic partitioning and state conict (battles between governmenttroops and rebels)
I ethnic partitioning and violence against civiliansI ethnic partitioning and foreign interventions by neighboring countries
I Robustness???
I Further Evidence???
I UCDP-GED database
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A Closer Look
I Results (so far):
I ethnic partitioning and state conict (battles between governmenttroops and rebels)
I ethnic partitioning and violence against civiliansI ethnic partitioning and foreign interventions by neighboring countries
I Robustness???
I Further Evidence???
I UCDP-GED database
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Data
I Source: Sundberg and Erik Melander (Journal of Peace Research,2013); Sundberg, Lindgren and Padskocimaite (2010)
I Coverage: 1989 2010. 11; 418 fatal incidents.
I
Event denition the incidence of the use of armed force by anorganized actor against another organized actor, or against civilians,resulting in at least 1 direct death in either the best, low or high
estimate categories at a specic location and for a specic temporal
duration
I state-driven conict: 7:332 (64:25%)
I non-state conict: 1:283 (11:25%)
I one-sided violence: 2:803 (24:5%)
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UCDP Conict Events by Type
Type of Violent Events UCDP 1989-2010
African Boundaries
Type of Violence
State Violence
Non-State Violence
One-Sided Violence
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Ethnic Partitioning and State Conict
All Homelands Homelands close to the BorderAll Events Indicator Duration All Events Indicator Duration
NB-ML LPM NB-ML NB-ML LPM NB-ML(1) (2) (3) (4) (5) (6)
SPLIT (Partitioning) 0.4978** 0.0487* 0.3390** 0.8053*** 0.0799** 0.5469**
Double-clustered s.e. (0.2411) (0.0294) (0.1422) (0.2335) (0.0393) (0.2389)
SPIL (Adjacent Split) 1.1577*** 0.0902* 0.6868** 0.434 0.0424 0.255Double-clustered s.e. (0.4761) (0.0518) (0.2964) (0.5468) (0.0534) (0.3744)
Log Likelihood -1453.054 -1046.922 -528.002 -383.392Observations 0.471 0.441
1212 1212 1212 579 579 579Simple Controls Yes Yes Yes Yes Yes YesLocation Controls Yes Yes Yes Yes Yes YesGeographic Controls Yes Yes Yes Yes Yes YesCountry Fixed Eects Yes Yes Yes Yes Yes Yes
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Ethnic Partitioning and Non-State Conict
All Homelands Homelands close to the BorderAll Events Indicator Duration All Events Indicator Duration
NB-ML LPM NB-ML NB-ML LPM NB-ML(1) (2) (3) (4) (5) (6)
SPLIT (Partitioning) -0.2087 -0.0459 0.026 -0.4122 -0.0351 -0.1797
Double-clustered s.e. (0.4062) (0.0317) (0.3374) (0.5178) (0.0283) (0.4917)
SPIL (Adjacent Split) -0.8703 -0.0344 -0.5089 -0.6593 -0.0268 -0.6964Double-clustered s.e. (0.7193) (0.0302) (0.4423) (0.8728) (0.0415) (0.7086)
Log Likelihood -841.675 -644.791 -243.97 -199.677Observations 0.320 0.310
894 1212 1212 415 579 579Simple Controls Yes Yes Yes Yes Yes YesLocation Controls Yes Yes Yes Yes Yes YesGeographic Controls Yes Yes Yes Yes Yes YesCountry Fixed Eects Yes Yes Yes Yes Yes Yes
The Long-Run Eects of the Scramble for AfricaEthnic Partitioning and Civil Conict. Results
UCDP-Based Results
E h i P i i i d O Sid d Vi l
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Ethnic Partitioning and One-Sided Violence
All Homelands Homelands close to the BorderAll Events Indicator Duration All Events Indicator Duration
NB-ML LPM NB-ML NB-ML LPM NB-ML(1) (2) (3) (4) (5) (6)
SPLIT (Partitioning) 0.3468 0.0269 0.2750* 0.3288 0.0331 0.2925
Double-clustered s.e. (0.2416) (0.0292) (0.1474) (0.2615) (0.0404) (0.2237)
SPIL (Adjacent Split) 0.4708 0.0829* 0.4935** 0.0901 0.0161 0.1659Double-clustered s.e. (0.4549) (0.0481) (0.2277) (0.6886) (0.0626) (0.3416)
Log Likelihood -1499.837 -1099.667 -556.79 -396.804Observations 0.404 0.434
1212 1212 1212 579 579 579Simple Controls Yes Yes Yes Yes Yes YesLocation Controls Yes Yes Yes Yes Yes YesGeographic Controls Yes Yes Yes Yes Yes YesCountry Fixed Eects Yes Yes Yes Yes Yes Yes
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UCDP-Based Results
T ki S k
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Taking Stock
I Strong link between ethnic partitioning and main aspects of civilconict (incidents, likelihood, duration, and fatalities).
I Predominant type of conict: government forces ghting againstrebels and militias (ACLED and UCDP).
I Strong link between ethnic partitioning and military interventions byneighboring countries (ACLED).
I Positive link between ethnic partitioning and one-sided violenceagainst civilians. (ACLED and UCDP).
I No link between ethnic partitioning and riots and protests.(ACLED).
I No link between ethnic partitioning and conict between non-stateactors. (UCDP).
The Long-Run Eects of the Scramble for Africa
Ethnic Partitioning and Ethnic Power (EPR)
EPR Database
E h i P R l i (EPR) D b
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Ethnic Power Relations (EPR) Database
I Source: Wimmer, Cederman and Min (Ethnic Politics and Armed Conict,American Sociological Review, 2009)
I
The Ethnic Power Relations (EPR) dataset identies all "politicallyrelevant ethnic groups" and records the level of access to statepower by their representatives in all countries of the world from1946 2010 (vintage 3).
I
Ethnic-based Armed ConictI Political discrimination
The Long-Run Eects of the Scramble for Africa
Ethnic Partitioning and Ethnic Power (EPR)
EPR Database
EPR D t b O t V i bl
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EPR Database. Outcome Variables
I Ethnic Armed Conict: "Ethnic wars typically involve conicts over ethnonationalself-determination, the ethnic balance of power in government, ethnoregional autonomy,
ethnic and racial discrimination (whether alleged or real), and language and other
cultural rights."
I Political discrimination: "Group members are subjected to active, intentional,and targeted discrimination with the intent of excluding them from both regional and
national power. Such active discrimination can be either formal or informal. Formal
discrimination legally limits access to government positions to citizens who speak a
certain mother tongue, display certain phenotypical features, or are members of certain
religious groups. Informal discrimination actively and intentionally inhibits individuals
with certain ethnic backgrounds from rising within the ranks of government."
The Long-Run Eects of the Scramble for Africa
Ethnic Partitioning and Ethnic Power (EPR)
EPR Database
Eth i P R l ti (EPR) D t b t C t
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Ethnic Power Relations (EPR) Database, cont. Caveats
I Manually matched 547 groups from EPR to Murdock (1959)
I Caveats:
I Matching is not straightforward as the EPR often quotes coalitions ofgroups
I EPR includes only politically relevant groups (may be a plus)
I An ethnic category is politically relevant if at least one signicantpolitical actor claims to represent the interests of that group in the
national political arena, or if members of an ethnic category aresystematically and intentionally discriminated against in the domainof public politics.
The Long-Run Eects of the Scramble for Africa
Ethnic Partitioning and Ethnic Power (EPR)
EPR Database
Ethnic Partitioning and Political Power
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Ethnic Partitioning and Political Power
Observ. Ethnic Wars Discrimination(1) (2) (3)
Partitioned Ethnicities 234 (0.395) 72 (0.31) 58 (0.248)
Non-Partitioned Ethnicities 359 (0.605) 69 (0.19) 52 (0.145)
Total 593 141 (0.238) 110 (0.185)
The Long-Run Eects of the Scramble for Africa
Ethnic Partitioning and Ethnic Power (EPR)
EPR Database
Examples
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Examples
Politically discriminated partitioned ethnic groups
I Tigrinya in Ethiopia
I
Asben in NigerI Ambo and Chokwe in Angola
I Zaghawa and Bideyat in Chad
I Ndau in Zimbabwe
I
Alur in UgandaI Yakoma in Central African Republic
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The Long-Run Eects of the Scramble for Africa
Ethnic Partitioning and Ethnic Power (EPR)
EPR Results
Ethnic Partitioning and Ethnic Political Discrimination
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Ethnic Partitioning and Ethnic Political Discrimination
LPM LPM LPM LPM(1) (2) (3) (4)
SPLIT (Partitioning) 0.1030*** 0.0778*** 0.0766*** 0.0718**Double-clustered s.e. (0.0342) (0.0276) (0.0289) (0.0282)
SPIL (Adjacent Split) 0.0169Double-clustered s.e. (0.0764)
adjusted R-square 0.018 0.475 0.495 0.521Observations 593 593 593 593Countries 40 40 40 40
Country Fixed Eects No Yes Yes YesSimple Controls No No Yes YesLocation Controls No No No YesGeographic Controls No No No Yes
The Long-Run Eects of the Scramble for Africa
Ethnic Partitioning and Ethnic Power (EPR)
EPR Results
EPR Analysis Results Summary
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EPR Analysis. Results Summary
I Direct evidence linking ethnic partitioning with discrimination fromthe national government
I
Link between ethnic partitioning and major ethnic-based civil warsover full post-independence period (further evidence on conict)
I The link between ethnic partitioning and ethnic wars is attenuatedwhen accounting for discrimination (though still signicant
conditional correlation)I SPLIT coef. (s.e.): 0:066 (0:035)
The Long-Run Eects of the Scramble for Africa
Ethnic Partitioning, Discrimination and Public Goods Provision (DHS)
DHS Data
Individual-Level Data
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Individual-Level Data
I 24 Sub-Saharan African countries; 300 ethnic groups in the DHS
I 1; 000 to 6; 000 respondents in each country. Out of 112; 737 males88; 171 were matched to 190 pre-colonial groups (Murdock, 1959).
I georeferenced data; at the enumeration area (village/town) level =>
match to ethnic homelandsI information on the ethnic location
I Focus on living conditions (including access to public goods)
I DHS composite wealth index (1 5): information on household
wealth; quantiles of wealth distribution within a countryI Education (0 5): "no education", "incomplete primary", "complete
primary", "incomplete secondary", "complete secondary", and"higher".
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The Long-Run Eects of the Scramble for Africa
Ethnic Partitioning, Discrimination and Public Goods Provision (DHS)
DHS Data
Identifying wiith Split Groups and Residing in Split
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Identifying wiith Split Groups and Residing in Split
Homelands
Non-Split Homeland Split Homeland Total
Non-Partitioned Ethnic Identity 36,694 13,256 49,950
Partitioned Ethnic Identity 12,590 25,631 38,221
Total 49,287 38,887 88,171
The Long-Run Eects of the Scramble for Africa
Ethnic Partitioning, Discrimination and Public Goods Provision (DHS)
DHS Baseline Results
Ethnic Partitioning and Individual Well-Being, DHS
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Ethnic Partitioning and Individual Well Being, DHS
Composite Wealth Index
All Observations (Individuals) Observations close to the Border(1) (2) (3) (4) (5) (6)
Ethnic Partitioning -0.3853*** -0.3227*** -0.1978** -0.2818*** -0.2679*** -0.2248**Double-clustered s.e. (0.1129) (0.0987) (0.0919) (0.1018) (0.0961) (0.0791)
Non-Indigenous 0.1936** 0.1942** 0.1825*** 0.1359* 0.1397* 0.1942**Double-clustered s.e. (0.0887) (0.0844) (0.0690) (0.0783) (0.0741) (0.0688)
Adjusted R-squared 0.028 0.072 0.167 0.053 0.090 0.162
Observations 88171 88171 88171 44090 44090 44090
Country Fixed Eects Yes Yes Yes Yes Yes YesIndividual Controls No Yes Yes No Yes YesLocation Controls No No Yes No No Yes
The Long-Run Eects of the Scramble for Africa
Ethnic Partitioning, Discrimination and Public Goods Provision (DHS)
DHS Baseline Results
Ethnic Partitioning and Individual Education
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Ethnic Partitioning and Individual Education
All Observations (Individuals) Observations close to the Border(1) (2) (3) (4) (5) (6)
Ethnic Partitioning -0.3166** -0.2238** -0.1482* -0.1726* -0.1493* -0.1242
Double-clustered s.e. (0.1297) (0.0938) (0.0811) (0.0976) (0.0869) (0.0758)
Non-Indigenous Indicator 0.1082 0.1163 0.1024 0.0568 0.0587 0.0813Double-clustered s.e. (0.0838) (0.0766) (0.0704) (0.0691) (0.0632) (0.0549)
Adjusted R-squared 0.151 0.222 0.255 0.132 0.188 0.210Observations 88171 88171 88171 44090 44090 44090
Country Fixed Eects Yes Yes Yes Yes Yes YesIndividual Controls No Yes Yes No Yes YesLocation Controls No No Yes No No Yes
The Long-Run Eects of the Scramble for Africa
Ethnic Partitioning, Discrimination and Public Goods Provision (DHS)
DHS Baseline Results
Ethnic Partitioning and Wealth: Identity versus Location
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g y
All Observations Border Observations(1) (2) (3) (4)
Partitioning - Identity -0.3122** -0.2078** -0.2893*** -0.2440***Double-clustered s.e. (0.1236) (0.0939) (0.1058) (0.0797)
Partitioning - Location -0.2275** 0.041 0.0346 0.0983Double-clustered s.e. (0.1134) (0.0811) (0.1364) (0.0815)
Non-ndigenous Indicator 0.1894** 0.1837*** 0.1371* 0.2013***Double-clustered s.e. (0.0911) (0.0684) (0.0771) (0.0671)
Adjusted R-square 0.032 0.167 0.053 0.162
Observations 88171 88171 44090 44090
Country Fixed Eects Yes Yes Yes YesIndividual Controls No Yes No YesLocation Controls No Yes No Yes
The Long-Run Eects of the Scramble for Africa
Ethnic Partitioning, Discrimination and Public Goods Provision (DHS)
DHS Baseline Results
Ethnic Partitioning and Education: Identity versus Location
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g y
All Observations Border Observations(1) (2) (3) (4)
Partitioning - Identity -0.2832** -0.1659* -0.1922* -0.1484*Double-clustered s.e. (0.1340) (0.0853) (0.1007) (0.0773)
Partitioning - Location -0.1039 0.0729 0.0904 0.1241**Double-clustered s.e. (0.0784) (0.0628) (0.0992) (0.0630)
Indigenous Indicator 0.1062 0.1047 0.0601 0.0903*Double-clustered s.e. (0.0852) (0.0696) (0.0665) (0.0526)
Adjusted R-squared 0.151 0.255 0.133 0.214
Observations 88171 88171 44090 44090
Country Fixed Eects Yes Yes Yes YesIndividual Controls No Yes No YesLocation Controls No Yes No Yes
The Long-Run Eects of the Scramble for Africa
Ethnic Partitioning, Discrimination and Public Goods Provision (DHS)
DHS Further Evidence
Ethnic Partitioning and Wealth Within-Village Variation
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g g
All Observations (Individuals) Observations close to the BorderComposite Wealth Index Education Composite Wealth Index Education
(1) (2) (3) (4) (5) (6) (7) (8)
Ethnic Partitioning -0.0665*** -0.0644*** -0.0856** -0.0799** -0.0541** -0.0506** -0.0680* -0.0582D ouble-clustere d s.e. (0.0196) (0.0196) (0.0364) (0.0347) (0.0237) (0.0243) (0.0407) (0.0396)
Non-Indigenous 0.0761*** 0.0729*** 0.039 0.0328 0.1027*** 0.1022*** 0.0212 0.0164D ouble-clustere d s.e. (0.0208) (0.0205) (0.0341) (0.0321) (0.0243) (0.0238) (0.0460) (0.0430)
Adjusted R-squared 0.694 0.696 0.463 0.482 0.656 0.658 0.416 0.435Observations 88171 88171 88171 88171 44090 44090 44090 44090
Village Fixed Eects Yes Yes Yes Yes Yes Yes Yes YesIndividual Controls No Yes No Yes No Yes No YesLocation Controls No Yes No Yes No Yes No Yes
The Long-Run Eects of the Scramble for Africa
Ethnic Partitioning, Discrimination and Public Goods Provision (DHS)
DHS Further Evidence
Ethnic Partitioning Wealth and Education. Non-Indigenous
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g g
All Movers Non-Split Homelands Split Homelands(1) (2) (3) (4) (5) (6)
Partitioning - Identity -0.2897* -0.1887** -0.4192** -0.1950* -0.1764** -0.1496**
Double-clustered s.e. (0.1499) (0.0928) (0.2115) (0.1112) (0.0841) (0.0758)
Partitioning - Location -0.1582* 0.0021Double-clustered s.e. (0.0833) (0.0675)
Adjusted R-squared 0.135 0.251 0.137 0.290 0.152 0.221Observations 53992 53992 30606 30606 23386 23386
Country Fixed Eects Yes Yes Yes Yes Yes YesIndividual Controls No Yes No Yes No YesLocation Controls No Yes No Yes No Yes
The Long-Run Eects of the Scramble for Africa
Ethnic Partitioning, Discrimination and Public Goods Provision (DHS)
DHS Further Evidence
DHS Analysis. Results Summary
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I Individuals identifying with partitioned groups have worse economicconditions and are less educated
I
even when we look across individuals residing in the same village/townI even when we look at "movers" (both in partitioned homelands and
non-split homelands)
I Location (ethnic partitioning) matters but not that much.
I Results apply to both "young" and "old" respondents (persistence)
The Long-Run Eects of the Scramble for Africa
Conclusion
Research Question and Approach
Main Contributions
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I Vast literature on the eects of colonization(type/identity/investments/infrastructure) on African(under)development.
I Recent works on the eects of the slave trades (Nunn (2008))
I Some work on the long-lasting of ethnic institutions (Michalopoulos andPapaioannou (2013))and other ethnic traits (Fenske (2013))and the legacyof historical conict (Besley and Reynal-Querol (2014))
I This paper: Focuses on the long-run eects of the Scramblefor Africa
I African historiography (e.g., Dowden (2008), Asiwaju (1985))
I so far have been neglected in economics (exception: Alesina et al. (2011))
The Long-Run Eects of the Scramble for Africa
Conclusion
Research Question and Approach
Main Contributions
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I Vast literature on the eects of colonization(type/identity/investments/infrastructure) on African(under)development.
I Recent works on the eects of the slave trades (Nunn (2008))
I Some work on the long-lasting of ethnic institutions (Michalopoulos andPapaioannou (2013))and other ethnic traits (Fenske (2013))and the legacyof historical conict (Besley and Reynal-Querol (2014))
I This paper: Focuses on the long-run eects of the Scramblefor Africa
I African historiography (e.g., Dowden (2008), Asiwaju (1985))
I so far have been neglected in economics (exception: Alesina et al. (2011))
The Long-Run Eects of the Scramble for Africa
Conclusion
Results Overview
Results Summary
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1. In the eve of colonization and African independence partitionedethnicities compared to non-partitioned groups
I were of similar levels of economic development
I
did not dier in pre-colonial institutional traitsI shared similar geographical features, except that the partitioned
groups had larger land and water areas
2. Since African independence partitioned ethnicities
I have experienced signicantly more
I civil conict
I violence towards civilians
The Long-Run Eects of the Scramble for Africa
Conclusion
Results Overview
Results Summary
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1. In the eve of colonization and African independence partitionedethnicities compared to non-partitioned groups
I were of similar levels of economic development
I
did not dier in pre-colonial institutional traitsI shared similar geographical features, except that the partitioned
groups had larger land and water areas
2. Since African independence partitioned ethnicities
I have experienced signicantly more
I civil conict
I violence towards civilians
The Long-Run Eects of the Scramble for Africa
Conclusion
Results Overview
Further Evidence. Channels
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I Interference by nearby countries mostly takes place in homelands ofpartitioned groups
I State-driven conict (government forces against rebels)
I Partitioning => political discrimination of split groups.
I Partitioning is associated with worse living conditions (access to
public goods) both for partitioned individuals irrespective of theirlocation
The Long-Run Eects of the Scramble for Africa
Conclusion
Results Overview
Future Research
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I Theoretical reconciliation (Esteban and Ray, 2011, 2012)
I Further understand the mechanisms (case studies, other outcomes,etc.)
I Focus on other regions, such as the Middle East (ISIS spread?)
I
Examine other aspects of state articiality (in Africa and elsewhere)
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