Political instability, political regimes and economic performance in African countries Jean-Claude Berthélemy*, Céline Kauffmann+, Laurence Renard° and Lucia Wegner+

First draft, 11 March 2002

Abstract This paper is based on the work carried out for the African Economic Outlook (2002), joint report recently published by the African Development Bank (ADB) and the OECD Development Centre. The original data are computed from the weekly newspaper Marchés Tropicaux et Méditerranéens. The paper uses the methodology first proposed by Dessus, Lafay and Morrisson in A Politico-economic Model for Stabilisation in Africa (Journal of African Economies, 1994). The qualitative information obtained from Marchés Tropicaux et Méditerranéens is used to construct three indicators referring to: 1. Political instability: based on occurrence of strikes, demonstrations, violence and coup d’état. 2. An index of the softening of the political regime derived from information on releases of political prisoners, measures in favour of human rights, decisions promoting democracy, lifting of bans on demonstrations and public debates. 3. A measure of hardening of the political regime based on incarcerations of opponents, measures threatening democracy such as dissolution of political parties, violence perpetrated by the police and the banning of demonstrations or public debates. The resulting database covers 22 African countries over the ADB 5 sub-regions of Africa in order to reach a sample representative of the continent, on a weekly basis from January 1996 to December 2001. Quarterly data is then computed to study the relationship between political unrest and the nature of the political regime while annual data is used to investigate the political and economic dynamics. The paper suggests a strong correlation between conflict and political regime. It also conveys the idea that economic performance in Africa interacts deeply with political factors. * Université Paris I Panthéon Sorbonne, France and OECD Development Centre + OECD Development Centre ° Université Paris I Panthéon Sorbonne, France

The OECD, the OECD Development Center and their member governments are not responsible for the 4opinions expressed in this paper.

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1. Introduction

Preventing conflicts is becoming a widespread objective in Africa as recent international evidence show an increase of crime and violence in developing countries and negative spillovers for neighboring economies are highlighted. Both at the international level (through the recent focus of World Bank on conflict and the work on helping prevent violent conflict at OECD Development Assistance Committee, DAC) and regionally (through the NEPAD, New Partnership for African Development), awareness of the dreadful effects of conflict is rising and the need for prevention tools is underlined.

Preventing conflict requires a good knowledge of the interaction between the economic sphere and the political one, as well as the dynamic of political decisions. It implies access to indicators that are informative about the risks of running into conflicts and that allow a close monitoring of fragile/unstable countries. DAC relates those risk indicators to the following aspects: -

loss of political space for opposition, civil society and media

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social, economic and political exclusion

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unemployment, especially among youth

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impoverishment

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increasing inequalities

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human rights violations

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increasing insecurities

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migratory flows

In this paper, we present a set of three political indicators based on the series of events displayed below. Those indicators allow us to investigate on a quarterly basis the dynamic of political institutions, their adaptation to social and political unrest and the resulting impact on economic performance for 22 African countries over a 6-year period, from 1996 to 2001. The objective is not to address the issue of conflicts in countries that are already affected, but to offer early warning and risk indicators for countries that are

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still relatively stable. As such, none of the countries covered by the paper are in a situation of open war, although one or two might drift towards such a situation.

1. Political instability: based on occurrence of strikes, demonstrations, violence and coup d’Etat.

2. An index of the softening of the political regime derived from information on releases of political prisoners, measures in favour of human rights, decisions promoting democracy, lifting of bans on demonstrations and public debates.

3. A measure of hardening of the political regime based on incarcerations of opponents, measures threatening democracy such as dissolution of political parties, violence perpetuated by police and banning of demonstrations or public debates.

As opposed to the traditional literature on this issue, our approach is not static. Traditionally, the empirical papers consider the impact of political characteristics on the economic performance or the politico-economic characteristics of countries at war. Here, we investigate the responses of the institutions to political and social unrest, namely whether the government chooses to respond by a softening or a hardening of the regime, and their implications at the institutional level and for economic performance.

The traditional approach is also partial as it mainly considers causality of political factors on economic performance, more rarely the reverse and even more rarely the correlation between institutional variables. The study of political factors is usually left to political sciences. This paper deals with the dynamic of political responses to political instability as well as their consequences for economic growth. We use causality tests to investigate the relationship between instability and the softening/hardening of the regime.

Most empirical papers on political environment and economic performance rely on yearly and aggregated data as a result of the constraint on macro-economic data. However, our dataset allows us to follow the countries on a quarterly basis. It also provides us with

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more detailed information on political institutions as the data are computed from events and do not derive from the perception of the democratic profile of the power.

In section 2, we survey the previous literature. Section 3 provides details on the quarterly data set on political events that we have built. Section 4 is devoted to tests of causality between political instability and political decisions made by the governments; it shows a bi-directional causality between political troubles and political hardening by the government. Based on annualized data, section 5 studies complementary economic determinants of political instability while section 6 studies the reverse impact of political instability on investment and economic growth. Section 7 concludes.

2. The literature on political environment and economic performance

The literature on the subject is relatively abundant on 2 aspects: civil wars and the impact of political background on economic performance. Whereas the first kind of papers tackles the issue of the incidence of conflicts, the causes and consequences of wars in countries that are affected, the second type of paper investigates the interaction between economic performance and political developments. Since this paper does not focus on countries at war, it then belongs to the second strand.

Political context and economic performance

Since North (1991), several economic papers have underlined the importance of the political environment for promoting economic development. Sound political institutions are believed to foster economic transactions mainly by reducing risks. However, controversies arise on what sound political institutions means and on the channels through which they impact economic performance. •

The uncertainty concerning the concept and the impact of democracy

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Of the two questions that arise from the debate on “sound political institutions”, one focuses on the generic notion of democracy as a synonymous for sound institutions. But, although democracy has been largely studied in the economic literature there is little agreement on its impact on economic performance. Barro (1991) and Özler and Rodrik (1992) disclose a significant and positive correlation between political freedom and economic performance. By contrast, Alesina and Perotti (1994) can not highlight any impact of democracy on growth, while Barro (1996) suggests a non-linear relationship, too much and not enough democracy being harmful to growth.

Such uncertainty is largely due to the fact that the concept of democracy covers many different realities and that apart from sharing a common poll system, democracies differ widely in their characteristics. As democracy, as well as dictatorship, reveals itself too broad a concept, one has to go down to the desaggregated features of the political regimes to be able to pin down properly the impact of political environment on economic development. In this paper, we consider three features of political institutions: hardening of the regime, softening of the regime and political instability, of which only the last one has been studied so far in the literature. •

The role of political instability

There is almost a consensus concerning the impact of political instability on growth, although the concept of instability itself is rather ambiguous. It covers both legal changes of heads of state and governments and violent take-overs. Whereas the first one refers to political changeover, the second one is more appropriately related to instability and has a broadly acknowledged negative impact on economic growth. That second concept includes elite instability, as defined by Fosu (1992) 1 , as well as less dramatic events linked to social unrest (demonstrations, political violence). Considering data availability, this paper mainly tackles the second sense of the concept of political instability.

1

It comprises for instance coup d’Etat as well as political plots.

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The negative correlation between political instability and growth can be explained through impaired production factors accumulation and efficiency, as underlined by Fosu (1992) and Dixit and Pindick (1994). Instability prevents political institutions from ensuring property rights, which in turn increases the probability that returns on investment are expropriated. As a result of higher risk, less investment is undertaken. Fosu (1992) shows that the same applies to human capital accumulation, as political instability might cause brain drain. In extreme cases of instability like revolutions or coups d’état, Fosu (1992) argues that breaks in the production process might occur, reducing directly the level of GDP. Moreover, the impact on production-factor accumulation can also be accompanied by a negative influence on their productivity. Indeed, the effect of investment and human capital accumulation on growth performance is likely to depend on the institutional context as efficiency of production factors is certainly improved in a stable environment.

Another channel through which political instability affects economic performance relates to political economy and consists in the reduction of time horizon that politicians might suffer when instability is high. In a context of high instability, politicians tend to avoid structural reforms and lead wait-and-see policies instead in order to limit disagreement with the population and the other political parties. A government can also choose to pursue the same economic policy in spite of all the evidence, in order to defeat its opponents. Such schemes have been developed in the political economic literature by Alesina and Tabellini (1989), Cukierman, Edwards and Tabellini (1992) and Ozler and Tabellini (1991). Following the same perspective, Clague, Keefer, Knack and Olson (1996) consider that short-term perspectives are not likely to help policy makers keep their commitments, while Murphy, Shleifer and Vishny (1991) and Terrones (1990) underline that a government threatened by instability may be tempted to use corruption to insure the loyalty of the bodies that might help it to remain in power like the police, the army, the administration...

Despite the diversity of the datasets as well as the methodologies used, the empirical studies suggest a significant negative correlation between political instability and

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economic growth (Barro, 1991, Alesina, Özler, Roubini and Swagel, 1996, Azam, Berthélemy and Calipel, 1996). Guillaumont, Guillaumont and Brun (1999) goes even further, showing that political instability combined with trade instability are the main factors behind the poor economic performance of African countries on 1970-1990. •

The channels

Concerning the channels, there is debate whether institutions affect economic performance directly or more indirectly, through production-factor efficiency and the establishment of an environment conducive for business. The inconclusive impact of democracy on growth points towards an indirect influence, as underlined by Tavares and Wacziarg (1997). The authors then turn towards more complex models than the traditional “Barro” one equation specification to justify the interlink between the economic and the political spheres. To that purpose, they systematically investigate nine channels through which they assume democracy might affect growth, using a simultaneous equations model. Two channels emerge as highly influential: through human capital accumulation and through political stability.

Fosu (1992) insists on the role of human capital accumulation as the channel through which political instability affects growth. He proves his point using multiplied (interactive) variables in the specification. De Haan and Siemann (1996) show that the impact through investment prevails since adding up and withdrawing this variable from the equation heavily influence the results. However, Guillaumont, Guillaumont and Brun (1999) question these results in the case of African countries and show that political instability, defined as a combination of coups d’état and foreign/civil wars, directly affects the residuals of the growth equation.

The determinants of political context

The channels are not the only issues at stake in the debate about political institutions and economic performance. Causality is also a major concern. Limongi and Przeworki (1993)

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justify the unclear impact of democracy on economic performance through methodological problems. They argue that it is impossible to compare the incidence of democracy and dictatorship holding everything else constant providing that dictatorships develop more easily when the economic situation is difficult. But because most studies limit the analysis to the impact of political factors on economic performance, completely overlooking one side of the relationship, they face simultaneity and endogeneity problems. By contrast, Limongi and Przeworki (1993) suggest that the economic context has a significant influence on the development of the institutions and might help justifying the settling of democracy. •

The economic determinants of institutions

The economic determinants of the political context have been little investigated in the economic literature. After Lipset (1959), economic development has been seen as an important factor in promoting political stability and democracy according to the argument that in wealthy societies, redistribution conflicts are defused. By contrast, the correlation between economic growth and political context remains unclear. While weak economic performance is likely to spark redistribution conflicts, a strong growth might destabilise the economy. At the empirical level, Barro (1996) and Tavares and Wacziarg (1997) confirmed the Lipset hypothesis on a cross section of countries and on panel data respectively while Alesina, Özler, Roubini and Swager (1996) did not find any evidence of a negative impact of a weak growth rate on political stability, underlining the contradictory effects of growth. •

The political factors

Among the political determinants of the institutional environment, democracy is considered to help strengthen political stability. Democracy involves rules and opposition force that reduce the risk of arbitrary decisions. Clague, Keefer, Knack and Olson (1996) underline that a democratic system is more likely to ensure the respect of property rights and the enforcement of contracts. Going back to Weber (1922), one can also argue that

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turnovers under democracies are less likely to bring political unrest since they are regulated by a legal framework. However, if democracy strengthens political stability, political stability is symmetrically more likely to help democracy settle. Few empirical studies tackle the interaction between the economic and the political spheres at a global level, taking into account the correlation between political factors. Among those frameworks, Tavarès and Wacziarg (1997) and Poirson (1998) confirm the negative correlation between democracy and political instability.

3. Construction of political indicators

In order to both follow through the political developments in the countries under study in the African Economic Outlook (2002), recently published by the African Development Bank and the OECD, and to assess the interaction between the institutional context and economic performance, three political indicators were computed. They were built on information taken from the weekly newspaper Marchés Tropicaux et Méditerranéens according to a methodology first proposed by Dessus, Lafay and Morisson (1994). The qualitative information derived from the newspaper was either computed as 0-1 variables with 0 being the non-occurrence of the event and 1 its occurrence or as 4-value indicators (with 0: non-occurrence, 1: occurrence but weak intensity, 2: medium intensity and 3: strong intensity). From these indicators, the three following main political indexes were constructed: an index of political instability and social unrest, a measure of the softening of the political regime and one of its hardening.

Political instability •

Strikes

0 = non-occurrence, 1 = 1 strike or number of strikers lower than 1 000 (included), 2 = 2 strikes or number of strikers between 1 000 and 5 000 (included), 3 = 3 strikes or number of strikers strictly higher than 5 000. •

Unrest and violence (number of dead and injured) Dead

0 = none, 9

1 = between 1 and 10 (not included), 2 = between 10 and 100 (not included), 3 = higher than 100. Injured

0 = none, 1 = between 1 and 50 (not included) or if the number of dead is between 1 and 10, 2 = between 50 and 500 (not included) or if the number of dead is between 10 and 100, 3 = higher than 500 or if the number of dead exceeds 100.

•

Demonstrations

0 = non-occurrence, 1 = 1 demonstration or number of strikers lower than 5 000 (not included), 2 = 2 demonstrations or number of strikers between 5 000 and 10 000 (not included), 3 = 3 demonstrations or number of strikers higher than 10 000. •

Coup d’état and attempted coup d’état

Softening of the political regime •

Lifting of state of emergency

•

Releases of political prisoners

•

Measures in favour of human rights

•

Improvement of political governance (fight against corruption…)

•

Relinquishment of political persecution, rehabilitation, return from exile

•

Political opening (measures in favour of democracy) 1 = Discussion with the opposition, 2 = Entry of the opposition to power, 3 = Opening of a regime to elections.

•

Lifting of bans on strikes or demonstration

•

Lifting of bans on press or public debates

10

Hardening of the political regime •

State of emergency

•

Arrests, incarcerations

0 = non-occurrence, 1 = between 1 and 10 (not included), 2 = between 10 and 100 (not included), 3 = higher than 100. •

Additional resources for the police, propaganda or censorship

•

Toughening of the political environment (expulsions, dismissals, curfew, dissolution of political parties…)

•

Violence perpetuated by the police (number of dead and injured) Dead 0 = none, 1 = between 1 and 10 (not included), 2 = between 10 and 100 (not included), 3 = higher or equal to 100. Injured 0 = none, 1 = between 1 and 50 (not included), 2 = between 50 and 500 (not included), 3 = higher or equal to 500.

•

Prosecutions, executions

•

Bans on strikes and demonstrations

•

Bans on press or public debates

•

Closing of schools

•

Forced demonstrations

The data were collected for the countries covered by the African Economic Outlook report (2002) as tools to precisely follow through the political developments in those countries. The sample is then highly driven by the reasons that prevailed in the choice of the report coverage. That coverage includes Botswana, Burkina Faso, Cameroon, Chad, Côte d’Ivoire, Egypt, Equatorial Guinea, Ethiopia, Gabon, Ghana, Kenya, Mali,

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Mauritius, Morocco, Mozambique, Namibia, Nigeria, Senegal, South Africa, Tanzania, Uganda and Zimbabwe. The most important countries in each of the continent’s five regions as defined by the African Development Bank 2 are among them as well as smaller countries to make the sample more representative. Nations involved in civil war have been left out mainly because of logistical problems. Consequently Central African countries are the least represented countries among Sub-Saharan countries. Similarly, the report’s look at North Africa, economically rather different from the rest of Africa, is limited to the two strongest economies: Egypt and Morocco. Overall, the sample accounts for 2/3 of the continent’s GDP and ¾ of its population.

The resulting database, firstly computed on a weekly basis – corresponding to the periodicity of Marchés Tropicaux et Méditerranéens –, was then aggregated on a quarterly basis in order to proceed with the statistical analysis. The weekly format would not be appropriate because of a lack of variance as the information collected on such a desagregated basis is very scarce.

A principal component analysis was undertaken in order to determine the set of relevant weights for the qualitative variables within the synthetic indexes. To that purpose, the dimensions of the different indicators were made homogenous. All 4-value indicators were split into 3 binary variables with one representing the occurrence of the event with weak intensity, the second binary indicator including weak and medium intensity and the third one the strong intensity. Table 1 - Weights in ‘Conflicts’ Strike Dead Injured Demonstration Coup d'état and attempt

low 0.53 0.76 0.77 0.61

medium 0.55 0.79 0.80 0.63

high 0.59 0.79 0.80 0.64

0.19

2

The five regions under consideration are North Africa, Western Africa, Central Africa, Eastern Africa and Southern Africa.

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Table 2 - Weights in ‘Softening of the political regime’ Lifting of state of emergency Releases of political prisoners Measures in favor of human rights Improvement of political governance Relinquishment of political persecution Political opening Lifting of bans on strikes or public debates

low

medium high

0.95

0.96

low

medium high

0.23 0.91 0.43

0.26 0.92 0.47

0.05 0.19 0.14 0.32 0.11 0.96

0.14

Table 3 - Weights in ‘Hardening of the political regime’ State of emergency Violence perpetuated by the police: Dead Injured Arrests Additional resources for the police Toughening of the political environment Prosecutions, executions Bans on strikes and demonstrations Closing of schools Forced demonstration

non-significant 0.26 0.93 0.47

non-significant 0.20 0.09 0.47 0.20 non-significant

4. The interaction between political instability and political hardening

Political instability is in practice the result of a combination of events that leads to social and political discontent. Among those factors, the political behaviour of the government plays a leading role. Very often, discontent is spurred by government decisions against political freedom. As a matter of fact, between 1996 and 2001, political tensions were highly correlated with more repressive political decisions in the countries under study. However, a reverse causation is also plausible if governments themselves decide to harden their policies in response to political dispute. In order to test these hypotheses, we have performed Granger tests, which

show that the correlation between political

instability and hardening of the regime is in fact bi-directional. As a consequence, political hardening and political instability reinforce each other. However, no correlation and no causality are found between instability and softening of the political regime (results not shown).

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These tests should be preferably performed at the national level, considering that each political system has its own dynamic behaviour. However, the number of observations constrains our causality tests. Therefore, we combine a global test, assembling all 22 countries, and tests performed at the regional level. Most of these tests provide significant results. The smallness of our North African and Central African samples helps explain the lack of significance of the tests for these regions. Table 4 – Results of the Granger causality tests

Sample

Number of observations

Instability => Hardening

Hardening => Instability

Opt. lag

F-stat

Opt. lag

F-stat

3

15.1 (.00)

Overall

462

3

16.2 (.00)

Western Africa

138

1

7.3 (.01)

Eastern Africa

115

1

13.4 (.00)

Central Africa

92

South Africa

115

North Africa

46

Non significant 2

Non significant 3

15.4 (.00) Non significant

6.8 (.01) Non significant

3

22.4 (.00) Non significant

Table 5 reports the corresponding estimated parameters for both causal regressions run on the overall sample. These results suggest a bigger impact of political hardening on instability than of instability on hardening: computed long term parameters are equal to 1.33 for the impact of hardening on instability and only 0.09 for the reverse impact. The smallness of the latter parameter suggests that the interaction between both variables will usually end up in a stable equilibrium, rather than in an unstable one, which would drive the economy in a vicious circle. This means that the mechanism uncovered by our data does not, in itself, lead to open conflicts. It may, however, exacerbate conflicts arising from political and economic shocks or mismanagement.

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Table 5 – Estimated parameter for the overall regressions

Political instability Hardening of the regime 1.37 0.51 (4.1) (4.6) 0.3 0.22 -7.6 (4.9)

Intercept Lagged dependent variable Lags of Hardening/Instability -1 -2 -3

-0.17 (1.1) 0.63 (4.6) 0.47 (3.4)

-0.007 (-0.5) 0.02 (1.6) 0.06 (5.1)

T-stat in parenthesis.

Some examples of the interactions between political instability and government policy may illustrate our results. As displayed in the following graphs, political instability has resulted in a reaction from the authorities in the case of Côte d’Ivoire during 1996, for Zimbabwe in 1998 and for Egypt and Chad throughout the period. Reciprocally, Nigeria displays a situation in which the hardening of the regime clearly explains the occurrence of political troubles, a pattern that also seems to be followed by Zimbabwe at the end of the period. South Africa exhibits contemporaneous correlation due to the immediate repression exerted by the authorities at the time of the troubles (mainly demonstrations and strikes).

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Chart 1. Political instability and hardening of the regime in 6 African countries

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-3 -4 2 3 1 4 00 00 01-0 01-0 01-0 01-0

1 3 -1 -2 -3 -4 -1 -2 -3 -4 -1 -2 -4 -1 -2 -3 -4 2 4 -4 -1 -2 -3 96 96 96 96 97 97 97 97 98 98 98-3 98 99 99 99 99 00 00 00 00 01-0 01-0 01-0 01-0

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Legend:

00 -4 01 -0 1 01 -02 01 -03 01 -0 4

00 -1 00 -2 00 -3

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Egypt

0

96 -1 96 -2 96 -3

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0

Nigeria --- Political instability

 Hardening of the political regime

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5. Economic factors explaining political instability Our results in previous section are only partial, as other variables may explain political instability. It is in particular tempting to test whether economic variables affect political instability. This is what is attempted in this section, again based on the data collected by the African Development Bank and the OECD for producing the African Economic Outlook. In doing so, we face an inevitable limitation, which is the lack of quarterly economic data. Therefore, we use a panel data estimation, based on yearly data (19962001) for our 22 countries. Results are reported in Table 6.

Table 6 - Political instability Political instability Hardening(-1) 1.49 (6.02) Growth (value) -15.56 (-1.81) Western Africa 7.27 (2.03) Southern Africa 5.73 (1.53) C .84 (.2) Nb of observations 110 Adjusted R² .40 T-stat in parenthesis.

As seen earlier, political instability is partly driven by the hardening of the regime. It is worth noting that the lagged value of political instability does not have a significant impact on its current level when included in the regression, while it was significant on a quarterly basis. This suggests that there is only a short period of persistence of political instability. Moreover, the parameter of Hardening, 1.49, is close to the long run value of the impact of Hardening on Instability computed from Table 5 (1.33). Although they are based on data with different frequencies, our analysis in this section and in previous section are therefore consistent.

In addition, the econometric test suggests that political factors are not only affected by political shocks but also by economic performance since growth displays a significant impact on political instability. Faster growing countries are less likely to experience political instability. While the literature on the subject does not provide any clear results, our tests show that for the African countries represented in our sample, growth has

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softened troubles instead of exacerbating them over the last 6 years. However, the relevant economic performance estimator is not the GDP growth in volume, but an indicator of growth in value, underlying the importance of shocks on revenues in explaining the discontent of the population. The impact of volume growth is much less significant (regression not shown).

6. Impact of instability on investment and growth

Going back to the ideas developed in the literature, one may want to check whether, in our dataset, political instability affects growth performance. The econometric tests carried out on our sample suggest that there is no direct impact of political factors (instability, hardening or softening) on growth but two indirect channels: through private investment and through a break in the coefficients in the growth equation.

Table 7 - Private investment Private Investment Growth 2.3 (3.7) Instability -.01 (-1.8) Western Africa .12 (.84) Eastern Africa .24 (1.65) Southern Africa .09 (.64) Northern Africa .32 (1.45) c -2.20 (-14.2) Nb of observations Adjusted R² T-stat in parenthesis.

132 .19

Political instability has a direct negative impact on the accumulation of private investment. This effect does not hold for public investment highlighting the fact that the two types of investment respond to different incentives. Private investment is highly sensitive to the institutional environment and the performance of the economy, hence justifying that both growth and instability are highly significant in the regression. On the contrary, public investment is a tool in the hands of the government to compensate for the lack of private investment and as such may have counter-cyclical behaviour.

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Chart 2. Private Investment and Political Tension

0.70

Equatorial Guinea 0.60

private investments

0.50

0.40

0.30

Gabon

0.20 Mauritius

Senegal 0.10

0.00 0.00

Egypt

Chad

10.00

Uganda

Mozambique

Tanzania

South Africa

Nigeria

Côte d'Ivoire

20.00

30.00

40.00

50.00

60.00

70.00

political tension

Political instability affects growth by hindering physical capital accumulation. It may also affect growth indirectly through the returns of investment, or directly through total factor productivity. Although political instability has no linear impact on growth (result not shown), a simple Chow test shows that the structural parameters of the growth equation are highly dependent on the level of troubles experienced by the countries. The break in the coefficients was tested in a systematic way by using all levels of political instability available in the database as potential thresholds. The Chow test was then performed on the sub-samples generated by such thresholds. It provided us with a series of Fisher statistics that helped us decide the relevance of a structural break and its occurrence in terms of the level of political instability. The cut-off point was inferred for the highest Fisher statistics. As a result, the strongest difference was found between countries with and without instability, rather than between countries with different levels of trouble.

Countries experiencing no political troubles display much higher returns to investment (structural parameter around 0.13) than countries with troubles (0.03). As a consequence,

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not only political instability hinders physical capital accumulation, it also alters its efficiency by reducing the impact of investment on growth.

Table 8 - Growth equation Growth Private Investment .04 (3.9) North Africa .15 (6.6) Oil producer .05 (3.0) C .13 (4.9) Nb of observations Adjusted R² Chow test T-stat in parenthesis.

132 .45

No troubles .13 (2.2) .17 (2.8) .04 (0.5) .30 (2.3)

Troubles .03 (5.4) .07 (4.7) .03 (3.8) .12 (8.7)

36 96 .48 .53 F(2,128)=20.53 (.000)

Consistently, the following graph shows clearly that over the period under study the trouble-free countries have experienced faster growth rates than the countries with political unrest. The only counter-example is 1996 for which there is no evidence of significantly different growth rates for both samples.

Chart 3. Economic growth and political instability No troubles

troubles

8

7

6

5

4

3

2

1

0 1996

1997

1998

1999

2000

2001

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7. Concluding remarks

This paper aimed at providing tools to both follow through and assess the dynamic of political institutions, their adaptation to political unrest and the resulting interaction with economic performance. Those tools were designed in the context of the African Economic Outlook project on a sample of 22 African countries over 1996-2001 and encompass three political indicators: political instability, hardening and softening of the regime. Simple descriptive analysis and econometrics on these indicators have clarified the dynamics of institutions and highlighted a high degree of interaction between political context and economic performance.

As illustrated by Granger causality tests, the 22 African countries covered in our analysis have experienced a bi-directional causality between political instability and hardening of the regime, suggesting that not only social unrest might lead to a hardening of the political stance of the government, but also that the behaviour of the leadership plays a key role in explaining the discontent of the population. It also appears that political softening does not create a reverse impact, suggesting the existence of a sort of hysteresis impact of political hardening.

Moreover, the econometric tests carried out suggest that political developments are not only driven by political events but are closely related to economic factors. For instance, growth seems to have softened political instability for the 22 African countries of our sample over 1996-2001, since countries that have experienced faster growth have been less exposed to troubles. Furthermore, the analysis on the reverse impact of political instability on investment and economic growth reveals that political tensions have a direct negative impact on the accumulation of private investments, affecting growth indirectly. Troubles also affect growth indirectly through a significant negative impact on the productivity of investment. It is shown, using a chow test, that countries experiencing no political instability display higher returns to investment than countries politically very unstable.

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