the consequences of divide-and-rule politics in africa south of the sahara

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The consequences of ‘divide-and-rule’ politics in Africa

Felix S. Bethke

University of Greifswald, Germany, [email protected]

Abstract

In post-colonial Africa many rulers relied on so called ‘divide-and-rule’ politics to survive in

office. The concept of divide-and-rule describes a strategy for rulers to sustain power by

breaking up rival concentrations of power into pieces that individually have less power than

the ruler implementing the strategy. In this paper I test the consequences of this kind of

leadership strategy. I use intentional cabinet shuffles as a proxy for ‘divide-and-rule’ politics

and test whether it is related to the probability of a coup d’état and the probability of

rebellion. The analysis reveals that while divide-and-rule politics decrease the risk of being

overthrown in a coup at the same time it increases the risk of rebellion.

Paper prepared for presentation at the Annual Meeting of the International Studies Association, Montreal, March 16-19, 2011.

Draft, please do not cite

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1 Preface

In post-colonial African politics many rulers relied on ‘divide-and-rule’ politics to survive in

office. The concept of divide-and-rule describes a strategy for rulers to sustain power by


the ruler implementing the strategy. A well known example of this kind of rule is Mobutu

Sese Seko, the leader of the Democratic Republic of the Congo from 1965 to 1997. By

frequently rotating government officials, Mobutu established a system of uncertainty and

vulnerability, where public officials were totally dependent on him (Acemoglu et al. 2004;

Leslie 1993). Another example is the rule of ‘Emperor’ Jean-Bédel Bokassa in the Central

African Republic. Bokassa, as Morrison et al (1989: 405) put it, made cabinet shuffling a

‘way of life’, assuming many portfolios by himself, just to hand them over to someone else in

the next reshuffle. These practices intensified the collective action problem for potential

opponents and thereby deterred any rival concentration of power.

However, the consequences of these ‘divide-and-rule’ politics as a strategy for

political survival are still opaque and not yet empirically analyzed in a systematic way. While

some scholars provided evidence that patronage politics in general lead to better regime

stability (Arriola 2009), others point to the fragile characteristics of this kind of rule and argue

that these regimes are especially prone to the occurrence of violent conflicts (Roessler 2011).

In this paper I will systematically test the consequences of ‘divide-and-rule’ politics. I

use intentional cabinet shuffles as a proxy and test whether it affects the probability of a coup

d’état and the probability of violent conflict. The analysis reveals that ‘divide-and-rule’

politics decrease the risk of being overthrown in a coup but at the same time it increases the

risk of rebellion.

The remainder of the paper is organized as follows. Section 2 describes the evolution of

political rule in Africa. Section 3 specifies the characteristics of ‘divide-and-rule’ politics and

reviews the literature on this topic. Section 4 describes the research design. Section 5 presents

the findings. Finally, Section 6 concludes.

2 Political rule in Africa

The origin of contemporary political institutions in Africa can be traced back to colonial rule.

The colonial powers implemented the division of Africa into modern states and sovereign

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territories respectively. Pre-colonial Africa had many ‘stateless’ society and even where states

existed, they were less formally defined than their modern counterparts. Therefore the

colonization period (in most cases from the Berlin Conference 1884/1885 through to the

1960s) had a remarkable impact on the continent and can be seen as the structural foundation

of contemporary African states (Chazan et al., 1999:42, Hyden, 2006). There are three major

consequences of colonial rule that shaped the development of political systems in African

states: (1) contradictions between traditional and colonial institutions; (2) the creation of non-

hegemonic states and (3) the swift decolonization process that produced fragile democratic

regimes.

The colonial powers established legal, political and administrative institutions, which

were generally alien to the existing African local realities. Traditional political institutions in

Africa ranged from consensus-based authority systems that used negotiation rather than

hierarchical procedures for public decision making to centralized systems of chieftaincy,

where all authority belongs to the elder (Ayittey, 1991). However, those traditional

institutions were either dissolved, suppressed or made instrumental to the colonial

administration. Accordingly, the chaining of traditional and colonial institutions created an

uneasy equilibrium of institutional contradictions.

Furthermore the state created by colonial rule was non-hegemonic in nature. European

colonialism had little interest to invest resources in administrative infrastructure. Accordingly

the administrative systems were of limited scope. The administrative structure consisted of

skeletal organizations, only large enough for the purposes of extracting revenues and ensuring

public order. Consequently, colonial governments did not develop any further capacity to

provide public goods like education or health care (Chazan, et al., 1999).

Finally, the mode of decolonization also shaped postcolonial political institutions. In

most of Africa the transition to independence was implemented unexpectedly swift. As

liberation and nationalist movements began to mobilize in the 1960s the imperial powers

quickly had to find a way to transfer power to indigenous governments. In most cases

negotiation talks proved to be key to independence. The result of these talks was usually the

agreement of the colonial authorities to oversee multi-party elections, with the winner of this

poll taking power under a new independence-constitution. All these new constitutions were

democratic in nature and a compromise between the major political actors and their respective

interests. However, when the new incumbents took office, they applied a ‘winner-takes-all’

logic and amended constitutions in their favor. Since the colonial state the people experienced

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for decades ruled authoritarian and coercive, there were no historical moorings for democracy

to build up on. Democratic institutions promoting representation, consultation, involvement

and participation of the people in governance and public administration did not have room to

grow. Correspondingly, in the first decade after independence, there was a reoccurrence of

autocratic rule on the continent and most of the fragile democratic regimes were swept aside.

The process of liberation most of the time culminated in authoritarian regimes relying heavily

on ‘strong’ leadership personalities (Hyden, 2006).

Scholars of African politics refer to such concepts as personal rule, clientelism and

neopatrimonialism to describe politics in postcolonial Africa (Chabal and Daloz, 1999). They

describe political rule as opportunistic and particularistic. State power is perceived as a

private good and the state is controlled and run for the benefit of those in power. However, to

explain the survival of these exclusionary regimes, scholars refer to the establishment of a

‘divide-and-rule’ strategy by authoritarian leaders.

3 Politics of Divide-and-Rule

In general the concept of ‘divide-and-rule’ describes a strategy for actors to sustain power by


the actor implementing the strategy. The roots of the concept, which is also known as ‘divide-

and-conquer’ or ‘divide et impera’, go far back to Chinese philosophy of war and it also

appears in Machiavelli’s classic work on the Art of War.

“A Captain ought, among all the other actions of his, endeavor with every art to divide the forces

of the enemy, either by making him suspicious of his men in whom he trusted, or by giving him

cause that he has to separate his forces, and, because of this, become weaker.” (Machiavelli,

[1521] 2003)

The German philosopher Immanuel Kant puts the concept in a more general context of political rule and specifies it as one of the main maxims for successful leadership:

“Divide et impera. That is, if there are certain privileged persons in your nation who have chosen you as their chief (primus inter pares), set them at variance with one another and embroil them with the people. Show the latter visions of greater freedom, and all will soon depend on your untrammeled will. Or if it is foreign states that concern you, it is a pretty safe means to sow discord among them so that, by seeming to protect the weaker, you can conquer them one after another.” (Kant, [1795] 2010)

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This instrument of political rule is discussed frequently among contemporary scholars of

politics in general and African politics in specific.

Studies of international politics and diplomacy refer to this strategy when an actor

actively tries to deter unification among co-contractor in international (trade) regimes (Chun,

2009, Nexon and Wright, 2007). For example Chun (2009) refers to Russia’s energy policy

towards the European Union as a strategy of divide-and-rule. Because of a lack of unity

among EU member states over energy security, Russia has been able to exert considerable

influence over EU policy (Chun, 2009: 333).

Scholars of history and political geography describe the strategy of ‘divide-and-rule’

as a main feature of colonial policies (Christopher, 1988, Morrock, 1973, Wesseling, 1996).

To secure their power and means of exploitation colonial authorities divided and rearranged

populations into discrete groups, on the basis of ethno-linguistic attributes. Scholars further

argue that this division of territory on ethnically defined lines caused many economic and

political crises in the former colonies after independence. For instance Belgium’s “divide-

and-rule” policy favoring the Tutsi in Burundi created the conception that Tutsi were born to

rule while the Hutu were an inferior race. This conception was later instrumented by a

regional group of Burundian leaders to capture and monopolize power, which contributed to

the grievances that lead to violent conflict between these groups (Sambanis 2003: 73).

Finally scholars of comparative politics use the concept to analyze the causes and

consequences of leadership strategies in different regions of the world (Acemoglu et al., 2004,

Konrad and Skaperdas, 2007, Seidmann, 2008, Seshia, 1998). Particularly suited for the

context of African politics, Acemoglu et al. (2004) developed a model of ‘divide-and-rule’ to

explain the survival of predatory rulers such as Mobutu Seko of Zaire.

In general Acemoglu et al. (2004) developed a model of ‘personal rule’ where they

assume, that leaders use a ‘divide-and-rule’ strategy to sustain their power. Building on the

seminal work of Jackson and Rosberg (1982) their model describes political behavior in

weakly institutionalized societies, where formal rules do not effectively constrain the behavior

of the ruler. In this setting, they argue, rulers effectively rely on ‘divide-and-rule’ politics.

Their theoretical model closely matches the situation of African political regimes from

independence in the 1960s until the third wave of democratization at the beginning of 1990s.

In the African context most scholars refer to clientelism or patron-client relationship as the

main informal political institution that governed the behavior of actors in the political realm

(Allen, 1995, Clapham, 1982, Sandbrook, 1998, van de Walle, 2007). Therefore, the strategy

of ‘divide-and-rule has to be analyzed within this context.

Clientelism is usually understood as a specific social relationship that is based on

informal rules. In the African context it usually refers to situations, were

power and exchange access to state funds for political support

Most scholars define

personal bonds between political patrons and their clients/followers

Goldsmith, 2002, Eisenstadt and Lemarchand, 1981, Kaufman, 1974, Lemarchand, 1972,

Lemarchand and Legg, 1972

exchange relationship between unequals

client are unequal actors and exchange unequal goods in their clientelistic relationship. The

patron controls resources, offering them to his clients

receives a political advantage, whereas the client receives a material benefit. Therefore,

clientelism is an exchange relationship, which is based on reciprocitivity by

mutually beneficial transactions. However, the patron has disproportionate power and some

autonomy about how he distributes his assets to

Eisenstadt and Lemarchand, 1981, Lemarchand, 1972, Lemarchand

relationship can be illustrated as a pyramid

Figure 1: Relationship between Patron and Client

1 Adapted from Scott, J. (1972) PatronPolitical Science Review 66.

Patron

Client Client

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rule has to be analyzed within this context.

is usually understood as a specific social relationship that is based on

In the African context it usually refers to situations, were

power and exchange access to state funds for political support.

clientelism as a dyadic relationship with a

personal bonds between political patrons and their clients/followers


Lemarchand and Legg, 1972, van de Walle, 2007). Furthermore, clientelism describes an

exchange relationship between unequals in terms of wealth, status or influence


trols resources, offering them to his clients for political support. Usually the patron


clientelism is an exchange relationship, which is based on reciprocitivity by


autonomy about how he distributes his assets to the clients (Brinkerhoff and Goldsmith, 2002,

Eisenstadt and Lemarchand, 1981, Lemarchand, 1972, Lemarchand and Legg, 1972)

relationship can be illustrated as a pyramid-network (see figure 1).

: Relationship between Patron and Client1

Scott, J. (1972) Patron-Clients Politics and Political Change in Southeast Asia.

Client

Patron

Broker

Client Client Client


is usually understood as a specific social relationship that is based on

rulers exploit their

with a complex chain of

personal bonds between political patrons and their clients/followers (Brinkerhoff and


. Furthermore, clientelism describes an

in terms of wealth, status or influence. Patron and


. Usually the patron


clientelism is an exchange relationship, which is based on reciprocitivity by involving


(Brinkerhoff and Goldsmith, 2002,

and Legg, 1972). The

Clients Politics and Political Change in Southeast Asia. American

Broker

Client Client

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At the top of this pyramid scheme is always the patron, who represents the ruler that

distributes resources to the clients at the lower level (left side of figure 1). If the scheme

becomes more complex, which means more actors become involved, the role of the broker

becomes relevant (right side of figure 1). Brokers perform as clients for the patron, but they

have clients at the lower level too, for which they are patrons. They receive resources from

the patron, which they can manage independently and distribute them among their clients.

There may be several levels of brokerage involved in the clientelistic pyramid.

Now within this framework a ruler does not have to fear any formal threats to his

leadership. He can neither be displaced through elections nor due to constitutional constrains,

since he is able to control both of these formal institutions and change them in his favor. Once

in power, African autocrats found numerous ways to win ‘elections’ either because they were

the only candidate, rewrote the results in their favor and/or intimidated and repressed

opposing candidates. At the same time they were busy at amending the constitution in their

favor or ignoring it in general (Jackson and Rosberg 1982). But although formal institutional

mechanisms to depose rulers are missing in clientelistic settings, informal constrains still

exist. Rulers face the threat of revolution and competition from other political elites. To

survive these threats rulers may employ ‘divide-and-rule’ politics, which Acemoglu et al.

(2004) describe in the form of selective taxation and cabinet shuffling.

The first mechanism, selective taxation, refers to the strategy of imposing punitive

rates of taxation on actors who want to dissent and redistributes the gains to other actors.

Since different actors need to cooperate in order to depose a ruler, this strategy provides

incentives for the single actor to defy from cooperation. If one group of actors challenges the

ruler, he will simply bribe the other groups with the rents that were originally meant to be

distributed to the group of challengers (Acemoglu, et al., 2004:180-83).

The second mechanism, cabinet shuffles, refers to the frequent exchange of ministers

and the political elite in general (Acemoglu, et al., 2004:170). As noted by van de Walle

(2001:105) cabinet changes were frequently used by African rulers as a strategy to manage

elite relations and ensure the loyalty of ministers. By frequently rotating ministers the ruler

demonstrates that the presence in the cabinet depends on his goodwill. Thereby he deters any

larger rival coalitions of power among ministers.

To analyze the consequences of divide-and-rule politics in comparative perspective, I

will focus on the effect of intentional cabinet shuffles. I conceptualize the organization of the

cabinet as a pyramid-scheme like the one illustrated above for the patron-client relationship.

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The respective ruler of a country represents the patron and the cabinet members represent a

broker position. Ministers are therefore seen as representatives for certain ethnic or social

groups within society that channel these interests into the political elite. Therefore, if a ruler

chooses to use ‘divide-and-rule’ politics in a patron-client relationship, he will dispel and

exchange the cabinet members frequently in order to avoid any accumulation of power by a

coalition of brokers. With own resources at their disposal, brokers can build up coalitions with

power and influence and thereby reach a position, where they can challenge the ruler.

However, since different actors need to cooperate in order to depose a ruler (collective action

problem), he may prevent this situation of organized action against him by reshuffling public

officials frequently. He thereby intensifies the collective action problem. A ruler wants to

sustain a cabinet constellation that is safe for him, in the sense that ministers are dependent on

his will and are only weakly connected to each other and their respective interest groups.

Therefore, once members of the political elite develop strong ties among each other or within

society, the ruler reshuffles the cabinet.

Probably the best example of how cabinet reshuffling may be used strategically is the

leadership of Mobutu Sese Seko of Zaire. By frequently rotating government officials,

Mobutu established a system of uncertainty and vulnerability (Leslie, 1987:70) Public

officials were totally dependent on him for selection and maintenance of power. From 1970-

1995 Mobutu reshuffled the cabinet more than 20 times, which means the cabinet changed

almost every year. With this ‘divide and rule’ strategy, Mobutu was able to survive in office.

Although various plots and coup attempts (i.e. 1971, 1975 and 1978) were made, none of

them was successful. However, while marginalizing insiders of the political elite and

dispelling possible opponents, Mobutu made his enemies to challenge him from outside the

regime. Armed rebellions in Zaire in 1975, 1977, 1983 and 1985 may be a seen as a

consequence of Mobutu’s ‘divide-and-rule’ politics. Similarly, cabinet reshuffling was used

by Jean-Bédel Bokassa of the Central African Republic to fortify his rule. In his frequent

cabinet shuffles Bokassa occasionally assumed ministerial positions by himself just to create

uncertainty among his clients, whether their position is safe. He managed to stay in office for

14 year, although many attempts were made to displace him (Morrison et al 1989: 407).

African rulers frequently used cabinet shuffling as an instrument of political power.

However, the consequences of this form of rule are not yet explored systematically, although

some empirical studies point to the relevance of ruler-elite relations for political survival and

stability of the political system as a whole.

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Arriola (2009) has shown that the tenure of African leaders is related to cabinet size

and appointment practices. Using a proportional hazard model, his analysis revealed that

appointing additional ministers to the cabinet lowers a leader’s risk of being displaced by

coup.

Furthermore, Roessler (2011) found that ethnic power relations, that is whether certain

groups are excluded from state power, are significantly related to the onset of civil war. Those

ethnic groups that are excluded from the government are more likely to rebel compared to

those included in the central government. His findings support the theoretical model

developed by Azam (2001), who argues that the distribution of goods to various ethnic groups

is particularly advantageous for the prevention of rebellions.

Building on Morrison et al. (1989: 123/124) I distinguish between two forms of

political instability, which I consider possible consequences of ‘divide-and-rule’ politics:

events of (violent) elite instability and events of (violent) mass instability.2 Elite instability

refers to an event of collective violence that is aimed at replacing a ruler. Furthermore it is

exercised by members of the political elite. It can be empirically observed in coups d’état

organized by members of the regime or the military. Mass instability, involves revolts or

revolutions in which the ruler and his supporters are attacked by insurgents in form of a rebel

group or protest movement. In contrast to elite instability, mass instability is initiated by

outsiders of the political elite who do not have access to state power and material benefits. I

assume, that elite and mass instability have distinct causes and dynamics which may also

contradict each other. As illustrated above, cabinet shuffling may decrease the probability of

elite instability while at the same time increase the probability of mass instability. Taking into

account the basic characteristics of divide-and-rule politics specified above, the following

hypotheses can be formulated, regarding the consequences of intentional cabinet shuffles.

When implementing the strategy of divide-and-rule, rulers prevent the concentration of

power among potential rivals within the political elite. Furthermore the ability of the elite to

act collectively is impeded to a great extent (Acemoglu, et al., 2004). In order to successfully

depose a leader, different members of the political elite have to join forces. I therefore expect

that when a ruler frequently exercises cabinet shuffles, the probability of a successful coup

should be reduced.

2 Morrision et al. (1989) also describe communal instability as a distinct type of political instability. However, this form of instability seems to be unrelated to divide-and-rule politics and is therefore excluded from the analysis.

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H1: Intentional cabinet shuffles reduce the probability of a successful coup.

However, the exclusion of actors may cause grievances among societal groups, because

associates or representatives of them are expelled. These grievances may increase the

probability for the creation of rebel groups that challenge the regime from outside the political

sphere via violent conflict. Whereas insiders of an African political regime enjoy preferential

access to state offices and associated spoils, outsiders are left to ‘languish in the wilderness’

(Bratton and van de Walle, 1994: 463). Those individuals who had once access to state power,

but got excluded in a cabinet shuffle by the ruler, should be motivated to challenge the ruler in

an armed rebellion (Roessler 2011).

H2: Intentional cabinet shuffles increase the probability of rebellion.

4 Data & Measurement

Dependent Variables

The data on coups and violent conflict comes from Bates and colleagues (2010), who

compiled a comprehensive dataset of events of political instability for African countries for

the period 1970-1995. I chose this dataset because it separates events of elite instability

(coups) and mass instability (rebellion).

The first dependent variable successful coup is coded as a dummy variable, which

takes a value of 1 if at least one successful coup took place during the year and 0 otherwise.

The second dependent variable rebellion is measured as a dummy variable that takes a value

of 1 if at least one domestic armed group exists and they are fighting with some entity. Since

the analysis is only interested in the onset of a rebellion I replaced all ongoing events with

missing values.

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Independent Variable

The main independent variable is a self-coded variable of intentional cabinet shuffles. Cabinet

shuffles were defined as any major change in the composition of ministers in the cabinet. I

coded a ‘major change’ as those situations where at least two cabinet posts are assumed by

new ministers. I focused on intentional changes to include only those events which are related

to a ‘divide-and-rule’ strategy. Therefore, cabinet changes which are based on circumstances

like illness or death of a cabinet member or are the result of retirement were excluded.

Because of possible endogeneity problems I also dropped all cabinet changes that took place

in a year of elections, executive change or political instability (coup / rebellion). Since the

employment of a divide-and-rule strategy requires a consolidation of power, I excluded those

country-years, were ruler was less than three years in office. Sources for the coding of the

variable include periodicals like Africa South of the Sahara and Africa Contemporary Record

for various years as well as media databases like Lexis Nexis.3 I employ two versions of the

variable in the statistical analysis. I use a binary-coding for the variable cabinet shuffle, which

takes the value of one if one or more intentional cabinet changes occurred during a year in the

respective country. This variable is meant to capture the effect of the single event of an

intentional cabinet shuffle on the probability of a successful coup or rebellion respectively.

Because of a possible direct association between a cabinet reshuffle and an event of political

instability I also test an average coding of the variable. Furthermore, the characteristics of

‘divide-and-rule’ politics indicate that the frequency of cabinet reshuffling is more important

than the single event. The variable cabinet shuffle (avg.) measures the average number of

intentional cabinet shuffles a leader employed during his tenure each year. This coding.

however, assumes that ‘divide-and-rule’ politics are a leadership characteristic, which may be

present more or less for different rulers but remains constant for the whole tenure of a leader.

Both versions of the main independent variable are lagged by one year.

Control-Variables

I use a set of control variables, which proved significant in previous studies on the causes of

coups and violent conflict. Additionally, the control variables are meant to capture factors that

possibly intervene into the relationship between cabinet reshuffling and the respective

dependent variable. I limit the control variables to keep the models parsimonious and avoid

3 The reliability of the coding is rather weak. Due to diverse reasons I was not able employ reliability checks yet, i.e. code the data multiple times. The amount of sources used to code the data is also rather limited.

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multicollinearity. The basic model includes variables measuring democracy, GDP per capita

and population size.

To control for the effect of regime-type on the relationship between cabinet reshuffling

and political instability I use the Polity IV dataset (Marshall et al., 2010) which measures the

extent to which a country has political institutions that can be considered as democratic. I

rescaled the data to a scale from 1 to 21 to avoid the inclusion of the value zero that is present

in the original scale, which ranges from -10 to 10. To analyze whether economic development

is a relevant predictor for political instability, I also include a variable measuring GDP per

capita in the basic model. Finally a variable measuring the size of the population is also

included in the basic model, because the effect of cabinet reshuffling may be different for

small or large populated states respectively. The data for GDP per capita as well as the

variable population size comes from the World Development Indicators (World Bank, 2004).

To reduce the influence of single country observation with very high values, I take the natural

log of both GDP per capita and population.

In additional models I also include a measure of primary commodity exports as

proportion of GDP, known as sxp (Fearon, 2005), to test whether the presence of loot-able

resources is related to political instability and/or does intervene into the relationship between

cabinet reshuffling and the respective dependent variable.

Additionally, I control for ethnic diversity, since divide-and-rule politics might have a

different effect in settings of ethnic fragmentation. Furthermore, various forms of political

instability are usually said to be caused by ethnic factors. To measure ethnic diversity I use

the index of ethno-linguistic fractionalization (ELF). It measures the probability that two

randomly chosen individuals within a country will be from different ethno-linguistic groups.

The ELF is scaled from 0 to 1, whereby higher values represent a more ethnically

fractionalized country. The data comes from the Fearon and Latin dataset (2003).

The summary statistics for the variables used in the analysis are shown in the appendix of

this paper in table 1. All control variables are lagged by one year.

5 Analysis

The hypotheses will be tested for an unbalanced sample of up to 46 countries in the time

period 1970-1995. I will analyze the effect of intentional cabinet shuffles in two steps. First, I

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will analyze if the single event of an intentional cabinet reshuffle has a significant effect on

the probability of a successful coup and the onset of rebellion respectively. Second, I will

analyze whether the average shuffling frequency of a leader affects the probability of a

successful coup and rebellion respectively. To examine the hypotheses, I use a logit

regression model. The estimation reports robust standard errors, clustered by country.

Table 2 presents the results for the empirical model that analyzes the relationship

between the single event of an intentional cabinet reshuffle and a successful coup. Model 1

shows the results for a bivariate logit model without any control variables. In Model 2-4 I add

relevant control variables to the model to test whether the effects are robust.

[Table 2]

Table 2 shows that there is a positive relationship between the event of an intentional cabinet

shuffle and the probability of a successful coup. However, this relationship is not statistically

significant. The other control variables also show the expected sign and therefore confirm

early studies on military coups (O'Kane, 1993, Tusalem, 2010). The time since last coup, the

GDP per capita and ethnic fractionalization are negatively associated with the occurrence of a

successful coup. However, none of the variables in the model are robust and/or statistically

significant.

Now table 3 presents the results for the empirical model that analyzes the relationship

between cabinet shuffles and rebellion.

[Table 3]

As shown in table 3, there is a significant positive relationship between the event of a cabinet

shuffle and the probability of a rebellion. The relationship is robust to the inclusion of control

variables. Again the control variables show the expected sign, although not all of them are

robust. Furthermore democracy significantly increases the probability of rebellion, which is a

somehow unexpected finding.

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Since single events of cabinet changes and shuffling may be plagued by endogeneity

problems, in the sense that the shuffling is directly related to the coup or rebellion, I proceed

by analyzing an average measure of cabinet shuffling as described in section 4.

In table 4 I analyze the relationship between average cabinet shuffling and successful coups.

[Table 4]

As shown in table 4, there is a significant negative relationship between the average number

of cabinet reshuffles a leader exercised during his tenure and the probability of a successful

coup. The relationship is robust to the inclusion of control variables. Again the control

variables show the expected sign, but despite GDP per capita are not robust and/or significant.

Finally table 5 shows the results for the analysis of the relationship between average

cabinet shuffling and rebellion.

[Table 5]

As shown in table 5, there is a significant positive relationship between the average number of

cabinet reshuffles a leader exercised during his tenure and the probability of a rebellion. The

relationship is robust to the inclusion of control variables. Again, democracy significantly

increases the probability of rebellion, confirming the unexpected finding from table 3.

6 Findings

The results provide certain detail on the consequences of divide-and-rule’ politics in post-

colonial Africa. The findings from chapter 5 suggest that the relationship between ‚divide-

and-rule‘ politics and political instability is ambiguous. Regarding the effect of cabinet

shuffles studied as a single event, the analysis suggests that there seems to be no systematic

relationship on the probability of a successful coup. However, the event of a cabinet shuffle

does seem to significantly increase the probability of rebellion. When divide-and-rule-politics

is conceptualized as a leadership characteristic and the variable is measured as the average

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number of cabinet reshuffles a leader exercised during his tenure each year, the results

become more straight-forward. Rulers who shuffled the cabinet often during their tenure seem

to be less at risk to be overthrown in a coup. The relationship is shown in figure 2.

Figure 3: The effect of cabinet reshuffling on successful coups4

The more cabinet shuffling a leader exercises during his tenure per year, the less is the

predicted probability to be overthrown in a coup. Coup attempts aimed to overthrow a ruler

are less likely to succeed because the political elite is too weak to act collectively against the

ruler. As shown in figure 3, the predicted probability of a successful coup decreases from

about 7% to 0.5% when the average rate of cabinet shuffles is increased from 0 to 1 shuffle

per year.

4 To generate the graph, I used the post-estimation command prgen, which is part of the SPost package for Stata developed by Long and Freese (2006). Prgen computes the predicted probabilities of a binary dependent variable for different values of the independent variable. For figure 2 I used the results from Model 2 in Table 4. All other variables, included in the model were held at mean values.

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However, the findings in chapter 5 on the relationship between intentional cabinet shuffling

and the onset of rebellion indicate, that in this case the effect of divide-and-rule politics is vice

versa. Figure 3 illustrates the effect of cabinet shuffling on the probability of violent conflict.

Figure 4: The effect of cabinet shuffling on rebellion5

As shown in figure 4, the predicted probability of rebellion increases from about 4% to 22%

when the average rate of cabinet shuffles is increased from 0 to 1 change per year. The more

often a ruler chooses to use intentional cabinet shuffles as an instrument for political survival

during his tenure, the higher is the probability that he is challenged from outside the political

regime through an armed rebellion.

Therefore the consequences of ‘divide-and-rule’ politics are twofold. It increases the

power of the ruler when compared to other members of the political elite but at the same time

it creates deprived outsiders that might challenge the ruler in an armed rebellion. A ruler who

5 For figure 3 I used the results from Model 2 in Table 5. All other variables, included in the model were held at mean values.

17

uses this kind of political strategy therefore has to carefully manage his relation to the

political elite.

The results from the control-variables are largely as expected from previous research,

although most of the control variables are not statistically significant. Only a high GDP per

capita significantly decreases the risk of being overthrown by a coup or rebellion respectively.

A somehow unexpected finding is the positive relationship between democracy and the

occurrence of violent conflict. The effect may be caused by the consequences of the third

wave of democratization. Many regime transitions in Africa after the end of the cold war

culminated in violent conflict among various factions. I made further tests (not reported here)

that included a dummy variable, which takes the value of 1 after 1989. When controlling for

this ‘Cold-War’ effect, the significant effect of democracy is no longer present. Additionally I

tested the squared term of the polity scale to account for a curve-linear relationship. The

analysis revealed that, consistent with the civil war literature (Hegre et al., 2001), the risk of

rebellion follows an inverted U-shaped curve, where strong autocracies and strong

democracies experience the lowest risk of rebellion, whereas hybrid regimes in the middle of

the scale are most prone to violent conflict.

7 Conclusion

This paper analyzed the main consequences of divide-and-rule politics in Africa for the period

of 1970 until 1995. It was shown that divide-and-rule politics as represented by intentional

cabinet shuffles were frequently used by African leaders as an instrument of political survival.

However, the consequences of this ruling strategy appear to be diverse. It deters the capability

of the cabinet to act collectively against the ruler and depose him in a palace coup but at the

same time when a ruler frequently excludes members of the political elite he creates deprived

outsiders that are more likely to challenge him in an armed rebellion.

However, the findings of this paper are only a first step in the analysis of cabinet

politics and their relationship to political instability. At least three major short-comings and

areas for further research can be identified:

First, the coding of the main explanatory variable needs further improvement. Both the

reliability and the coverage of the data need to be improved to get an accurate picture on the

consequences of cabinet changes. To address these issues a re-coding of the data that includes

18

more sources as well as covering more years seems like a promising strategy. Furthermore the

analysis might also benefit from more a fine-grained coding that not only includes cabinet

shuffling but precise data on rulers practices of appointment and dismissal of ministers as

well.

Second, the exclusion of the military from the theoretical framework as well as

empirical analysis is a major problem that needs to be addressed. The military is an important

actor in in coup d’états. Most coups were exercised by military personal and in many cases

the military is also the main initiator behind the coup. Furthermore, military involvement into

politics is also an important factor, that might influence the shape and success of divide-and-

rule politics.

Third, the approximation of ‘divide-and-rule’ politics with intentional cabinet changes

only tells one part of the story. ‘Divide-and-Rule’ politics is more than cabinet changes.

Especially the allocation of state funds by the ruler and his distribution of public offices

among clients go beyond cabinet positions. The leadership of Tubman in Liberia is an

example that illustrates the shortcomings of the focus on cabinet data. With the beginning of

Tubman’s presidency in 1943 a significant shift in power occurred. Tubman implemented

amendments to the constitution that strengthened presidential power. However, he made use

of clientelism to sustain his leadership. He appointed so called ‘Public Relations Officers’ as

his clients, who acted as a network of informers supplying information and comments on local

administrators (Clapham, 1982, Liebenow, 1969, Sawyer, 1992). The creation of special

advisor positions that operate outside the cabinet but carry out important functions for the

leader and thereby accumulate political influence is quite common in African politics and

should be incorporated in further attempts to assess the consequences of ‘divide-and-rule’

politics

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Appendix

Table 1: Summary Statistics

Variable Obs Mean Std. Dev. Min Max

Successful Coup 1194 .038 .192 0 1

Rebellion 990 .093 .29 0 1

Time since last Coup 1194 9.382 7.224 0 25

Time since last Rebellion 990 6.995 6.196 0 25

Cabinet Shuffle 945 .412 .492 0 1

Cabinet Shuffle (avg.) 972 .366 .196 0 .984

Polity 1027 6.249 5.113 1 21

Population (log) 1186 15.003 1.551 10.889 18.527

GDP per capita (log) 1020 7.28 .694 5.767 9.262

Primary Commodity Exports 970 .19 .14 .0124 .568

Ethno-linguistic Fractionalization 962 .6451351 .2442428 .04 .93

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Table 2: dependent variable 'successful coup'

(1) (2) (3) (4) Cabinet Shuffle 0.262

(1.47) 0.162 (0.80)

0.265 (1.32)

0.216 (0.94)

Time since last coup -0.0735***

(-2.61) -0.0554* (-1.68)

-0.0544 (-1.50)

-0.0503 (-1.52)

Polity 0.0236

(0.61) 0.0293 (0.72)

0.0303 (0.82)

Population (log) 0.0764

(0.42) 0.207 (0.82)

0.135 (0.70)

GDP per capita (log) -0.555

(-1.61) -0.454 (-1.00)

-0.745** (-2.06)

Ethno-linguistic Fractionalization -1.140*

(-1.70)

Primary Commodity exports -0.0777

(-0.05) _cons -2.770***

(-9.70) -0.253 (-0.06)

-2.401 (-0.39)

0.126 (0.03)

Observations 943 834 772 751 pseudo R-sq 0.030 0.032 0.049 0.043 t statistics in parentheses; * p<0.10, ** p<0.05, *** p<0.01

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Table 3: dependent variable 'rebellion'

(1) (2) (3) (4) Cabinet Shuffle 0.555***

(2.75) 0.508** (2.28)

0.689** (2.48)

0.661** (2.22)

Time since last Rebellion -0.0111

(-0.42) 0.00584 (0.19)

-0.00571 (-0.18)

0.0222 (0.76)

Polity 0.0430**

(2.10) 0.0507**

(2.56) 0.0528**

(2.42) Population (log) 0.125

(1.04) 0.121 (0.74)

0.202 (1.36)

GDP per capita (log) -0.648**

(-1.98) -0.609 (-1.50)

-0.675** (-2.00)

ethno-linguistic fractionalization -0.306

(-0.50)

primary commodity exports -3.047

(-1.38) _cons -2.580***

(-7.68) -0.286 (-0.09)

-0.366 (-0.08)

-0.996 (-0.31)


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Table 4: dependent variable 'successful coup'

(1) (2) (3) (4) Cabinet Shuffle (avg.) -2.023**

(-2.43) -2.543** (-2.01)

-2.068** (-2.04)

-2.388** (-2.42)

Time since last coup -0.0363

(-1.46) -0.0204 (-0.59)

-0.0245 (-0.68)

-0.0171 (-0.53)

Polity -0.00716

(-0.14) 0.0100 (0.20)

0.00643 (0.14)

Population (log) -0.0745

(-0.26) 0.0802 (0.22)

0.0599 (0.21)

GDP per capita (log) -0.858**

(-1.99) -0.759 (-1.42)

-1.161** (-2.50)

Ethno-linguistic Fractionalization -1.047

(-1.48)

Primary Commodity Exports 0.512

(0.23) _cons -2.346***

(-7.12) 4.976 (0.74)

2.278 (0.28)

4.851 (0.86)


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Table 5: dependent variable 'rebellion'

(1) (2) (3) (4) Cabinet Shuffle (avg.) 1.852***

(3.64) 1.686***

(2.58) 1.940** (2.37)

1.496** (2.56)

Time since last coup -0.00928

(-0.36) 0.00460 (0.15)

-0.00652 (-0.21)

0.0169 (0.59)

Polity 0.0517**

(2.13) 0.0569**

(2.30) 0.0549**

(2.19) Population (log) 0.0812

(0.70) 0.125 (0.84)

0.186 (1.36)

GDP per capita (log) -0.575*

(-1.83) -0.541 (-1.33)

-0.581* (-1.69)

Ethno-linguistic Fractionalization -0.744

(-1.09)

Primary Commodity Exports -2.886

(-1.27) _cons -3.033***

(-7.50) -0.600 (-0.20)

-1.092 (-0.24)

-1.693 (-0.55)


the consequences of divide-and-rule politics in africa south of the sahara

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