On the Probability of Military
Rule, Africa 1970-2007
Raul Caruso, Catholic University of Milan
Jacopo Costa, University of Florence
Roberto Ricciuti, University of Verona and CESifo
Outline
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Introduction
Models
Data and methodology
Results
Conclusions
Introduction
• Since the start of the so-called third wave in 1974, and the
acceleration after the fall of the Berlin Wall in 1989,
democratization has been impressive.
• According to the Economist Intelligence Unit (2011), one-half of
the world’s population now lives in a democracy of some sort.
More specifically, 12.3% lives in full democracies, 37.2% in
flawed democracies, 14.0% in hybrid regimes, and still 36.5% in
authoritarian regimes.
• Authoritarian regimes, in which the military plays a direct (when
a junta rules the country) and indirect role (when the army
guarantees the monopoly of violence for a civilian despotic
government), are the second largest regime group. A similar
ancillary role can be found in hybrid regimes.
• Freedom House (2009) reports that among the
48 countries of sub-Saharan Africa, 10 (21%)
were rated Free in calendar year 2008, while 23
were rated Partly Free (48%) and 15 were rated
Not Free (31%).
• This compares with the results in 1980, when 4
were rated Free (9%), 15 were ranked Partly
Free (32%), and 27 were ranked Not Free (59%),
showing some improvements.
Theory
• Acemoglu, Ticchi, and Vindigni (2010),
Besley and Persson (2010): agency
problem between the military and the
government.
• Main variables affecting military rule:
income, external threat, ethnic
fragmentation.
• The economy consists of two groups: the rich elite
and the citizens, distinguished by their incomes.
• Democracy leads to redistributive policies, in
particular, to the provision of public goods that are
beneficial for the citizens and costly for the rich elite.
• Starting from an oligarchy in which they hold power,
the elite are unwilling to allow a transition to
democracy. The only way they can prevent this is by
creating a specialized unit of the state, the military,
responsible for using force and repressing demands
for democratization.
• A powerful military also creates a political moral
hazard problem because it can turn against the elite
and take direct control of the government.
• The elite have three potential strategies in
oligarchy: no repression, thus allowing a
rapid transition to democracy; repression,
while also paying soldiers an efficiency
wage so as to prevent military takeovers;
and repression without significant
concessions to soldiers, thus opting for
nonprevention or facing the risk of a
military takeover.
• If a democracy inherits a large military from the previous
nondemocratic regime, then it will also be confronted
with a choice between making concessions to the
military and facing a coup threat.
• The decisive voter in a democracy wishes to prevent
coups, but if soldiers realize that democracy will reform
the military, reducing their rents. Since democracy
cannot commit to not reforming the military, it can only
make current concessions to soldiers and current
concessions may not be sufficient to compensate the
soldiers for the prospect of a military dictatorship.
• Consequently, societies in which nondemocratic regimes
in the past have chosen large militaries may have
difficulty consolidating democracy and may end up with
military dictatorships.
• In an oligarchy, whether the elite prefer to set up a
large military depends on the effectiveness of the
military and on the extent of inequality. When the
military is not very effective or inequality is limited,
the elite prefer to allow a smooth transition to
democracy, because such a regime will not be
highly redistributive (while repression is likely to fail).
• When military repression is likely to be effective and
there is sufficient inequality, the elite may prefer to
build a large military for repression and deal with the
political agency problem by paying the military an
efficiency wage.
• Natural resources increase the political
stakes because soldiers will be able to
capture the natural resource rents if they
take power.
• As a result, natural resource abundance
makes democracies more likely to fall to
military coups.
Model and data
• We estimated the following panel data
random effect probit model:
Militaryit = α1 + α2Xit + α3Zit + α4Wit + α5Pit
+ α6Sit + α7Cit + εit
• We consider 48 African countries over the
period 1970-2007.
• The dependent variable is a dummy equal to one in case
the ruler is a Military and zero otherwise (Database of
Political Institutions 2010).
• The vector Xit includes GDP per capita, derived from
Penn World Tables 6.3, and the added value of the
agricultural, manufacturing and mining sector as
percentage of GDP, using the UNCTAD database.
• The vector Zit includes variables concerned with ethnic
fragmentation, distinguishing between polarization and
fractionalization (Reynal-Querol).
• Wit is a vector including variables concerned with the
external sector: openness, from the Penn World Tables
6.3) and the intensity of external treat, defined as level of
hostilities on a 1-to-5 scale (Militarized Interstate
Disputes 3.10).
• The vector Pit includes the Agricultural Raw Price, taken
from Free Market Price Index, and the Crude Oil Price,
derived from Free Market Price Index (calculated as the
average of Dubai/Brent/Texas equally weighted
($/barrel)) from UNCTAD.
• Sit is a vector consisting of urban violence – using the
“Urban Social Disturbance in Africa and Asia” data,
reporting the unrest of social violence in the more
relevant city into every state (PRIO). We have also
considered the growth rate of population from Penn
World Tables 6.3 and a dummy for if landlocked
countries.
• Cit is a vector of dummy variables describing the colonial
rule of a country.
• εit is a random error.
• Continuous variables are in logs.
Existence of Military Rule, baseline results
GDP per capita
1
-.717***
(.120)
2
-201*
(.123)
3
-.386***
(.146)
Manufacturing share of GDP
Mining share of GDP
4
5
6
7
8
9
10
.284***
(.102)
.022
(.042)
.072
(.176)
-.108
(.076)
.329***
(.106)
-.077**
(.038)
.202**
(.0921)
.0101
(.0419)
.708***
(.115)
.37***
(.0995)
.648***
(.104)
1.503***
(.172)
.448***
(.127)
-.157
(.128)
-.017
(.118)
-.020
(.035)
.820***
(.121)
.0451
(.0700)
.951***
(.1349)
-1.28***
(.157)
.010
(.129)
Agriculture share of GDP
Polarization
Fractionalization
.617***
(.137)
-.586***
(.138)
Openness
Intensity of External threat
Crude Oil Price
Agricultural raw price
-.050
(.033)
-.155
(.155)
-.453
(.344)
.794***
(120)
-.498***
(.110)
-.363***
(.0821)
-.284***
(.0997)
.465***
(.136)
-.698***
(.148)
-.053
(.035)
-.158
(.159)
-.467
(.348)
Urban Violence
Landlocked
France
Belgium
-.003
(.0346)
-.169
(.158)
-.303
(.342)
.757***
(.221)
-.632***
(.284)
-.581***
(.211)
.104
(.217)
1.158***
(.262)
.277**
(.129)
-.297***
(.105)
-.340***
(.123)
-.26***
(.0903)
-.238**
(.117)
-.205
(.320)
.155
(.138)
-.918***
(.176)
1.005***
(.167)
-.003
(.108)
.462***
(.122)
.079
(.500)
-.015
(.0945)
.111
(.083)
Population growth rate
UK
.133
(.118)
-.038
(.116)
-.322
(.325)
1.361***
(.274)
1.246
(.396)
-.042
(.0269)
.009
(.111)
-.332***
(.071)
-.005
(.0899)
Existence of Military Rule, baseline results 2
GDP per capita
Manufacturing share of GDP
1
-.24**
(.118)
.56***
(.101)
2
-.03
(.147)
.343***
(.103)
3
.02
(.175)
.59***
(.117)
1.04***
(.168)
.626***
(.113)
-.304***
(.107)
.132
(.092)
.80***
(.163)
.982***
(.127)
-1.007***
(.131)
-.05
(.09)
1.08***
(.167)
.49***
(.135)
-.35***
(.125)
4
-.11
(.191)
.64***
(.121)
-.0315
(.056)
1.024
(.168)
.91***
(.152)
-.81***
(.149)
-.002
(.035)
-.180
(.157)
.677***
(.152)
-1.29***
(.187)
.058
(.162)
-4.25***
(1.83)
1106
-406.218
183.63
-.031
(.036)
-.183
(.157)
-1.00
(.138)
-.237
(.167)
1.12***
(.191)
-3.86**
(1.90)
1105
-409.222
140.79
Mining share of GDP
Agriculture share of GDP
Polarization
Fractionalization
Openness
Intensity of External threat
Crude Oil Price
Landlocked
UK
France
const
Obs.
Log Likelihood
Wald χ2
-2.78**
(1.40)
1353
-532.627
118.65
-.24***
(.101)
-.61***
(.116)
-.45***
(.159)
.466***
(.159)
-2.20
(1.64)
1353
-511.889
115.06
Existence of Military Rule, interactions
GDP per capita
1
-.46***
(.98)
2
-.57***
(130)
GDP per capita square
Manufacturing share of GDP
3
6.58***
(1.597)
-.497***
(.111)
.235***
(.099)
4
6.95***
(1.70)
-.538***
(.119)
.337***
(.113)
5
-.45
(.124)
6
-.68***
(.126)
7
.004
(.148)
8
-.336***
(.145)
.467
(.115)
9
4.03***
(1.757)
-.298***
(.124)
.363***
(.122)
10
4.78***
(1.473)
-.369***
(.103)
Mining share of GDP
Agriculture share of GDP
.698***
(.170)
Polarization
.280**
(.147)
-.388***
(.088)
.351***
(.076)
-.068
(.081)
-.064
(.080)
Fractionalization
Openness * manufacturing
.085***
(.027)
Openness * agriculture
.067**
(.033)
Fractionalization* manufacturing
Polarization* agriculture
France
Belgium
const
.101***
(.036)
-.149***
(.065)
.100***
(.020)
External threat * fractionalization
UK
.098***
(.034)
.038
(.027)
-.41***
(.162)
1.41***
(.169)
.948***
(.203)
2.32***
(.696)
.171*** .168*** .156***
(.059)
(.058)
(.060)
-1.10***
-.332
.148
-.613***
(.208)
(.243)
(.214)
(.189)
1.129*** .851*** 1.014*** 1.171***
(.167)
(.176)
(.191)
(.188)
1.53*** .815***
.446**
.814***
(.288)
(.247)
(.249)
(.250)
3.46*** -22.68*** -23.24***
.678
(.910)
(5.695)
(6.01)
(1.14)
.151***
(.057)
-.872***
(.200)
-.091
(.189)
.787***
(.237)
3.64***
(.861)
.154***
(.058)
-.85***
(.195)
-.103
(.189)
.989***
(.229)
-1.92
(1.38)
.075***
(.0228)
.125**
(.059)
-.272
(.226)
.988***
(.198)
1.79***
(.245)
1.07
(1.02)
.102*
(.060)
.0185
(.0399)
.170***
(.064)
-.642*** -.416***
(.206)
(.179)
-.274
1.04***
(.187)
(.186)
.545** 2.241***
(.263)
(.249)
-16.97*** -15.72***
(6.14)
(5.237)
Existence of Military Rule, lagged independent variables
GDP per capita t-1
GDP per capita t-5
Manufacturing share of GDP t-1
Manufacturing share of GDP t-5
Mining share of GDP t-1
Mining share of GDP t-5
1
-.588***
(.252)
.283
(.263)
.261**
(.140)
.237**
(.126)
.075
(.082)
-.273***
(.082)
.515***
(.171)
.214
(.140)
.223**
(.124)
.127
(.087)
-.354***
(.088)
.302**
(.143)
.201*
.128
.254***
(.086)
-.258***
(.0835)
.643***
(.127)
1.05***
(.300)
-.061
(.300)
.136
(.118)
-.187
(.123)
-.133
(.115)
Primary sector share of GDP t-1
Primary sector share of GDP t-5
Polarization
Fractionalization
openess t-1
openess t-5
Intensity of External threat t-1
Intensity of External threat t-5
Crude Oil Price t-1
Crude Oil Price t-5
Agricultural raw price t-1
2
3
4
.632***
(.180)
-.207
(.207)
.149
(.108)
-.334***
(.110)
5
.0784
(.314)
.189
(.326)
.595***
(.189)
-.308*
(.186)
.207**
(.111)
-.414***
(.114)
.902***
(.299)
.014
(.319)
.394***
(.121)
.973***
(.373)
.033
(.394)
.308**
(.155)
-.474***
(.128)
-.015***
(.004)
.008***
(.003)
.214
(.161)
-.015***
(.004)
.012***
(.004)
-.0168
(.0378)
.065
(.041)
6
8
9
.483***
(.173)
-.263
(.179)
.393***
(.111)
-.191*
(.109)
7
.005
(.314)
.660**
(.343)
.281
(.176)
-.412**
(.184)
.220**
(.109)
-.449***
(.116)
.675***
(.251)
.303*
(.179)
-.463***
(.181)
.194**
(.107)
-.441***
(.111)
-.460**
(.242)
.434**
(.180)
-.520***
(.196)
.389***
(.111)
-.300***
(.111)
1.157***
(.395)
.130
(.400)
.483***
(.154)
1.125***
(.357)
.338
(.377)
.479***
(.145)
.672*
(.378)
.169
(.402)
.606***
(.149)
.928***
(.367)
.060
(.387)
.783***
(.158)
.971***
(.376)
-.275
(.411)
.623***
(.171)
-.220
(.162)
-.013***
(.004)
.017***
(.005)
-.003
(.038)
.093**
(.0428)
-.330**
(.152)
-.015***
(.004)
.011***
(.004)
-.01
(.038)
.102***
(.041)
-.300*
(.177)
-.020
(.090)
-.865***
(.152)
-.018***
(.004)
.013***
(.005)
.006
(.038)
.120***
(.043)
-.351**
(.183)
-.030
(.094)
-.358**
(.162)
-.015***
(.004)
.013***
(.004)
-.007
(.039)
.103***
(.043)
-.380**
(.182)
-.006
(.0934)
-.572***
(.194)
-.016***
(.004)
.013***
(.005)
.019
(.039)
.110***
(.042)
-.205
(.183)
.471***
(.150)
-.0189
(.429)
Conclusions
• Income per capita negatively affects MR,
with some nonlinearities.
• Manufacturing and primary are positively
related with MR.
• Polarization and fractionalization have
opposite effects (+/-).
• Openness negatively affects MR.
• External threat becomes significantly
positive only when lagged.
• Crude oil price negatively affect MR,
whereas agricultural price are usually non
significant.