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Determinants of Political Instability in ECOWAS (1991–2022)

  • Richard Uzoma Gbemudia ORCID logo EMAIL logo and Stanley Uche Akachukwu ORCID logo
Published/Copyright: October 20, 2025
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Statistics, Politics and Policy
From the journal Statistics, Politics and Policy Volume 16 Issue 3

Abstract

This study examined GDP per Capita, military expenditure, trade openness capital formation, inflation and unemployment as determinants of political instability in ECOWAS from 1991 to 2022. Four countries in ECOWAS that have experienced military coup/political instability (Burkina Faso, Guinea, Mali and Niger) and another four countries that have not had military coup (Cote dÍvore, Ghana, Nigeria and Togo) were used for the study. The article modeled the independent equations for each country to show how the various countries’ cross-sectional indicators/variables affect political instability. Findings show that the major determinants of political instability in ECOWAS are GDP per Capita, military expenditure, and trade openness. GDP per Capita is negatively related to political instability in Burkina Faso, Guinea, Mali and Niger. A 1 %, increase in GDP leads to a, 0.067 %. 0.002 %, 0.001 % and 0.041 % in Burkina Faso, Guinea, Mali and Niger respectively. Military expenditure has a negative influence on political instability in Burkina Faso, and Niger but positively influences in Mali. A 1 %, increase in military expenditure in Burkina Faso and Niger reduces political instability by 0.196 % and 0.045 % respectively. Trade openness positively impacts on political instability in Burkina Faso, Guinea, and Mali. The statistics illustrate that a % increase in trade openness leads to about 0.0925 %, 0.029 % and 0.625 % in Burkina Faso in Burkina Faso, Guinea, and Mali respectively. Hence, GDP per Capita, military expenditure, trade openness, and unemployment are the main drivers of political instability in the region. The results from the four countries that did not experience democratic reversal during the study period reveal that GDP per capita, military expenditure and unemployment are significant and inversely related to political instability. The results from the aggregate analysis of the countries without military coups show that military expenditure (0.155 %), unemployment (0.164 %) and GDPC (0.00045 %) are significant and inversely related to political instability in these countries. This suggests that these countries are susceptible to political instability. Thus, the study recommends that governments in the ECOWAS region should invest in people-oriented projects to lift citizens out of poverty, cater adequately for security agencies and minimize undue interference in their economy’s economic, political and social structure by foreign actors.

Keywords: ECOWAS; political instability; military expenditure; GDP per capita; military intervention

1 Introduction

The Economic Community of West African States (ECOWAS) subregion[1] is currently witnessing problems in the practice of democracy.[2] Problems such as weak democratic institutions, corruption, bad governance, poor and underperforming economy, electoral malpractices, radical Islamist movements,[3] social inequalities and political violence have all contributed to the democratic setbacks in the region. According to Mhaka (2023), at least four countries in the Economic Community of West African States (ECOWAS) have experienced a military coup and an unlawful leadership change. Coups in Niger (2023), Mali (2021 and 2020), Guinea (2021), and Burkina Faso (2022) have raised questions about the future of the practice of democracy in the region (Obinna and Semudara 2024; Ojo 2023; Sowale 2024). Elections, which are one of the major cornerstones of democracy, are being threatened in the subregion and are marred by violence, intimidation, and conflict. In Nigeria, for example, the 2023 general elections were marred by many electoral malpractices and political violence. The Armed Conflict Location & Event Data Project (ACLED)[4] reported that in the months preceding the 2023 general elections in Nigeria, over 200 violent events involving party members and supporters resulted in nearly 100 reported fatalities (Armed Conflict Location & Event Data Project 2023). Also, presidents of Côte d’Ivoire, Guinea, and Togo have all breached the constitutionally required term limit in their quest to sustain power. All these problems contravene the Supplementary Protocol,[5] , [6] on Democracy and Good Governance, adopted in 2001 by ECOWAS.

Studies on democracy and political instability in the West African Sub-region have, from different perspectives[7] discussed security, economic, domestic and foreign influences as contributing factors causing the decline of democracy in the sub-region. Despite the abundant research on democracy and political instability in the region, there is a dearth of studies on the comparative analysis of determinants of political instability between states in ECOWAS. Therefore, this study examines four countries in ECOWAS that have experienced military coup/political instability (Burkina Faso, Guinea, Mali and Niger) and four[8] countries that have not had a military coup (Cote d’Ivoire, Ghana, Nigeria and Togo) to understand the cross-sectional indicators/variables (include GDP per Capita, capital formation, military expenditure, inflation, trade openness, and unemployment) that affect political instability in the various countries. Hence, in addressing the objective of the study, the segments discussed include an introduction, conceptual clarifications, literature review, the theoretical framework, the methodology, discussions on countries with military coups in ECOWAS, and discussions of ECOWAS countries without military coups during the period under consideration, results presentation, discussions of findings, conclusion and recommendations.

2 Conceptual Clarifications

2.1 Understanding the Concept of Political Instability

There is no one agreed-upon definition of political instability. The concept has different interpretations based on its usage. The concept of political instability has been defined from different perspectives. For example, the National Bureau of Economic Research (2023) defined political instability from an economic perspective to mean the propensity of a government to collapse. Alesina et al. (1996) conceptualise it as the change of the executive either by constitutional or unconstitutional means. Aurore (2012:3) defines political instability as “a sum of political events including assassinations, strikes, guerrillas, government crisis, purges, riots, anti-government demonstrations and revolutions”. Mbaku (1988) defined political instability as either a change in the existing political system or a challenge. Morrison and Stevenson (1971) define political instability as a condition in political arrangements in which the institutional structure of authority breaks down and the political authority is replaced by political violence. Jannils (2021) opines that political instability coincides with the instability of policies or the instability of institutions.

Furthermore, Jong-A-Pin (2009) differentiates between four dimensions of political instability: politically motivated violence, mass civil protests, instability within the political regime, and instability of the political regime. Morrison and Stevenson (1971) conceive political instability as a condition in political arrangements where the institutional structure of authority breaks down and the expected compliance with political authority is replaced by political violence aided by conflict involving elites, communal groups, and mass movements.

Political instability could also portray a situation whereby a polity is rendered ungovernable due to conflict, political violence, wars, natural disasters, etc. When a polity experiences political instability, in some cases, it means the democratic governance processes (the executive, legislature, and judiciary) are non-functional. Nigeria, for example, in its First Republic, the political instability in the country resulted in the collapse of the First Republic.

Political instability affects the economy, leading to high inflation, insecurity, and unemployment. For example, the conflict in Syria caused political instability and made the country ungovernable. Countries such Central African Republic and the Niger Republic are examples of countries that have experienced political instability on the continent.

For this study, we define political instability as the extent to which the distribution of power within a polity is challenged by internal or external political forces or actors, causing democratic reversal. These dynamics can be triggered by economic malaise, social injustices, polarised politics, weak institutions, or external shocks. Hence, some countries like Nigeria, Cameroon, and South Africa that are experiencing some sort of political violence, insecurity, and conflict cannot be classified as politically unstable states because of the proper function of their government and the conduct of periodic elections. Thus, it is in this light that Burkina Faso, Guinea, Mali and Niger are used as case studies of politically unstable countries in the ECOWAS sub-region.

2.2 Understanding the Concept of Military Coups

Military coups or coup d’état, sometimes known as military intervention, can be conceptualised as the intervention of the military against civilian administrations. Put differently, it is the involvement of the armed forces of a nation in the administration and governance of a particular state. This intervention results in the suspension of the constitution and other democratic institutions. Military coups can be violent or nonviolent. It can also be successful or unsuccessful. For example, in Nigeria, there have been seven successful military coups and many failed coup attempts. During military coups, the military rules through promulgating decrees.

3 Literature Review

Different studies have been conducted on the determinants of political instability in the ECOWAS subregion. Abu and Karim (2015) examined the causal relationship among corruption, political instability, and economic development in ECOWAS countries within a multivariate cointegration and error-correction framework. The findings of this study suggest that years of political instability have contributed to the high rate of corruption and underdevelopment in ECOWAS countries. The study concluded that High levels of corruption and underdevelopment in ECOWAS have been blamed on political instability, primarily resulting from many years of military rule. Fafore (2019) examined Radical Islam and Transnational Security in West Africa. The study concluded that the activities of armed Islamic movements are harming the economy and security of the states and people of West Africa. Obisie-Orlu (2022), in his study, argues that recent military coups in West Africa are rooted in poor governance. Marc et al. (2015) examined the challenges of fragility and security in West Africa. The study concluded that development policies have a critical role to play in improving stability where conflict risks are high.

Okafor and Okafor (2015) examined the major impediments to democracy in West Africa. From their study, they concluded that the reason remains that weak responses and social neglect from the government created a burning desire in the masses to demand a change of government, of which some consider mutiny or military involvement as a veritable option towards overthrowing an adamant regime that is conceived in a self-seeking drive. From a different perspective, Ajala (2023) studied the crisis of Democracy in West Africa and the Sahel. He concluded that the increased spotlight on the corruption and lack of development in the countries experiencing coups and the relationship with the former colonial power are reasons for political instability in the region. Abu et al. (2014) examined the causal relationship between corruption, political instability, and economic development in the ECOWAS states. The paper applied multivariate cointegration and Granger causality methodology to data from 1996 to 2012. The result shows that political instability Granger-causes corruption in the long run in ECOWAS countries. It also recommends that the ECOWAS government should employ policies to promote political stability in the region. Al-Jabri et al. (2022) investigate the influence of unemployment and democracy on youth bulges and political instability using data spanning 1984 to 2019 in over 100 countries. The analysis shows that a youth bulge enhances political instability, and unemployment worsens political instability. The analysis samples indicate that the youth bulge in democratic states stimulates political instability in North East and North Africa (MENA) and the Organisation for Economic Cooperation of Development (OECD). Al-Shammari and Willoughby examined the determinants of political instability in 19 Arab Spring countries between 1991 and 2014. They utilised pooled ordinary least squares, fixed, and random effect methodological techniques. The results show that food price shock (inflation), unemployment, and regime durability explained the political instability in the Middle East and North Africa (MENA) region. The youth bulge phenomenon does not explain political instability in the region.

From a different perspective, Chigozie and Oyinmiebi (2022) examined the resurgence of military coups in West Africa. They concluded that the failure of democracy in the region is largely due to the absence of credible elections, disregard for the rule of law, and the dominance of one-party rule, which together justify the recent coups. Similarly, Akinyemi et al. (2024) argued that the historical mishandling of conflicts and acts of impunity by governments are also key factors driving the resurgence of military coups in West Africa.

4 The Theoretical Framework

The underlying theoretical framework for this study is based on structural functional theory. This theory has its roots in sociology and is traced to the arguments of various scholars such as Talcott Parsons, Radcliffe-Brown, Herbert Spencer, Emile Durkheim, Auguste Comte, and Robert Merton, among others. The analogy employed in this approach was borrowed from the biological sciences, explaining how organs play specific roles for the survival of the organism. Hence, there exists a kind of interconnectivity that binds them. Each of these organs serves a unique function for the organism’s survival. This theory facilitates the study of society with a focus on explaining order and stability to maintain equilibrium. Applying this theory to modern society reveals that it views society as composed of different social structures working in concert for stability. Therefore, dysfunction in one social structure will impact the entire system.

The theory offers perspectives on human behaviour and its influence on society. It illustrates how social structure (socio-political environment) acts as both a tool and a consequence of actions taken by economic agents. The manner in which society is structured by its government through established standards, values, power dynamics, and rules dictates the actions of these economic agents. The theory acknowledges that economic agents operate within the context of rules established by social structures, and by acting in accordance with these rules, they reinforce these structures. In many countries that have faced political instability, challenges arise from the social structure’s weaknesses. Most institutions are inadequate and underperforming, making the country susceptible to military coups.

Political instability results from the reactions of economic agents to the social structure. Political instability is a characteristic of political economy, influenced by the various ways economic agents respond, which are shaped by the nature of the political economy. The theory highlights the interconnectedness of variables within the political economy. This suggests that military coups do not happen in isolation; they are instigated by other elements or variables that contribute to political instability. Functionalism posits that when institutions effectively perform their roles – such as well-funded militaries deterring threats, electoral systems ensuring legitimate transfers of power, and robust markets providing employment – they support one another and uphold democratic equilibrium. Conversely, ECOWAS states with fragile economic and security institutions have struggled to maintain this systemic balance, leading to democratic backsliding. Military coups within the ECOWAS region represent failures not just of the military but of the systemic coherence required for stability. The data from this study indicate that low military expenditure and high unemployment correlate strongly with coups, highlighting systemic functional breakdowns in governance structures.

In the ECOWAS region, we observe that:

  1. Weak military institutions (low military expenditure) correlate with a higher likelihood of coups. A poorly funded military cannot fulfil its defensive “organ” function, permitting dysfunction in the political “organ” (executive) through coups.

  2. Economic fragility (low GDP per capita, high unemployment) strains social and political structures, undermining democratic cohesion.

These observations resonate with the structural functionalist premise that when one structure underperforms, the entire system destabilises. Using structural functionalism, this study contextualises coups not merely as isolated occurrences, but as systemic breakdowns linked to interdependent structural failures in economic, political, and military institutions.

5 Methodology and Data

5.1 Model Specification

To capture the instability in ECOWAS, the study considered some possible drivers related to political instability.

(1) PIS B it = λ i 0 + λ 11 ϕ it + u it

where PISBit denotes political instability in i-number of countries at any given time. ϕ it is the vector that captures all the control or exogenous variables used in the study. λ 11 represents the vector that shows the sensitivity of the control variables for the i-countries used in the model. u it is an error term that captures other variables not included in the model. λ i0 represents the constant term that shows the least political instability each country could have, assuming the control variables are not taken into consideration in the model.

Equation (1) contains the vector of independent variables (ϕ it) which include GDP per Capita, capital formation, military expenditure, inflation, trade openness, and unemployment. Expanding eqn. (1) and factoring out the exogenous variables yields:

(2) PIS B it = λ 10 + λ 11 GDP C it + λ 12 CAP F it + λ 13 ME X it + λ 14 IN F it + λ 15 TOPN X it + λ 16 ≤ it + u it

Equation (2) states that political instability in the ECOWAS is driven by GDP per Capita (GDPCit), capital formation (CAPFit), military expenditure (MEXIT), inflation (INFit), trade openness (TOPNXit), and unemployment (UPMit). Where PISBit, GDPCit, CAPFit, MEXit, INFit, TOPNXit, UPMit represent GDP per Capita, capital formation, military expenditure, inflation, trade openness, and unemployment respectively across the ECOWAS. λ 11 , λ 12 ,   λ 13 ,   λ 14 ,   λ 15 ,   λ 16 indicate the sensitivity or coefficients that show how the GDPCit, CAPFit, MEXIT, INFit, TOPNXit, UPMit impact political instability in ECOWAS.

The study considers four countries in ECOWAS that have experienced military coup/political instability (Burkina Faso, Guinea, Mali and Niger) and another four countries that have not had military coup (Cote dÍvore, Ghana, Nigeria and Togo) over the study period. Hence, the study modeled the independent equations for each country to show how the cross-sectional indicators/variables affect political instability in the various countries. This is expressed below.

(3) PIS B t BF = λ 10 + λ 11 GDP C t BF + λ 12 CAP F t BF + λ 13 ME X t BF + λ 14 IN F t BF + λ 15 TOPN X t BF + λ 16 UP M t BF + u 1 t

(4) PIS B t GN = λ 20 + λ 21 GDP C t GN + λ 22 CAP F t GN + λ 23 ME X t GN + λ 24 IN F t GN + λ 25 TOPN X t GN + λ 26 UP M t GN + u 2 t

(5) PIS B t ML = λ 30 + λ 31 GDP C t ML + λ 32 CAP F t ML + λ 33 ME X t ML + λ 34 IN F t ML + λ 35 TOPN X t ML + λ 36 UP M t ML + u 3 t

(6) PIS B t NG = λ 40 + λ 41 GDP C t NG + λ 42 CAP F t NG + λ 43 ME X t NG + λ 44 IN F t NG + λ 45 TOPN X t NG + λ 46 UP M t NG + u 4 t

5.2 Countries without Coups

(7) PIS B t CT = λ 10 + λ 11 GDP C t CT + λ 12 CAP F t CT + λ 13 ME X t CT + λ 14 IN F t CT + λ 15 TOPN X t CT + λ 16 UP M t CT + u 1 t

(8) PIS B t GH = λ 20 + λ 21 GDP C t GH + λ 22 CAP F t GH + λ 23 ME X t GH + λ 24 IN F t GH + λ 25 TOPN X t GH + λ 26 UP M t GH + u 2 t

(9) PIS B t NR = λ 30 + λ 31 GDP C t NR + λ 32 CAP F t NR + λ 33 ME X t NR + λ 34 IN F t NR + λ 35 TOPN X t NR + λ 36 UP M t NR + u 3 t

(10) PIS B t TG = λ 40 + λ 41 GDP C t TG + λ 42 CAP F t TG + λ 43 ME X t TG + λ 44 IN F t TG + λ 45 TOPN X t TG + λ 46 UP M t TG + u 4 t

where BF, GN, ML, NG, CT, GH, NR and TG are Burkina Faso, Guinea, Mali, Niger, Cote d’Ivoire, Ghana, Nigeria and Togo respectively.

We applied the pool fixed effect analysis to estimate each group to ascertain if coups are driven by the same factor(s) or otherwise. Imperatively, we could not apply the Random Fixed Effect model because our N is small and less than the exogenous variables in the model. The study applied the Seemingly Unrelated Regression (SUR) model to ascertain country-by-country responses to the factors that determine military coups in ECOWAS.

5.3 Estimation Technique and Data Sources

The structural-functional theory provided the framework. The study applied the Seemingly Unrelated Regression (SUR) model proposed by Zellner (1962). The Seemingly Unrelated Regression model was used to explore the determinants of military coups in ECOWAS because this study required the estimation of multiple related equations. It is instructive to note that independent equations-by-equations OLS estimation may be biased in this study. This is due to the likely correlation between exogenous variables and the disturbance error (endogeneity bias) and serial dependence of the error term in cross-sectional data. In this study, the two assumptions may fail under the ECOWAS integration, due to the fact, ECOWAS member states share several economic and political characteristics in common, such as trade patterns and relations, institutions, colonial system, etc. These countries share borders. During crises, internally displaced persons can easily find refuge in the neighbouring countries. This is experienced in Nigeria and Niger. Insurgency dislodged in one country can move to the neighboring country. Trade and commerce are exchanged among the ECOWAS. Hence, the study requires a system equation that methodologically takes cognizance of the serial correlation between the exogenous variable and the error term. There are many methods of estimating system equations that involve heterogeneous units in the literature such as panel VAR (appropriate when assume that all variables in the system are endogenous), Dynamic panel (when lag of exogenous variables is also part of the independent variable), and SUR method (suitable when N is small, and T is large or infinite).

The SUR model is the most appropriate for this study because our N[9] < (less than) T[10] i.e. (N is small and T is large). The study could not use a dynamic panel because the study does not include the lag of the exogenous variable as one of the independent variables. Panel VAR cannot be operational in this study because one of its assumptions is that all variables in the system are endogenous which is not the case here. Therefore, SUR becomes the suitable estimation method for this study, where we have four (4) heterogeneous units and thirty-two (32) observations.

Four countries from ECOWAS that experienced military coups were considered: Burkina Faso (BF), Guinea (GN), Mali (ML) and Niger (NG). The political instability_PISBit (Military coups) and its determinants (GDP per Capita-GDPC, capital formation-CAPF, military expenditure-MEX, inflation-INF, trade openness-TOPNX, Unemployment-UPM) were explored. Pool and system equation models were estimated for the countries with military coups in ECOWAS using annual data from 1991 to 2022. Data were obtained from the World Bank (World Bank Development Indicator 2024, International World Integrated Trade 2024). All estimates were validated at α ≤ 0.05.

5.3.1 Econometric Underpinning: Seemingly Unrelated Regression Model

The Seemingly Unrelated Regression (SUR) model, introduced by Zellner and Huang (1962), is an econometric technique used when a set of regression equations is contemporaneously correlated by their error terms, even though they may seem unrelated at first glance. SUR is appropriate when the regressors are assumed to be exogenous and the errors are heteroscedastic and contemporaneously correlated (Orji et al. 2014). The SUR method estimates the parameters of all equations simultaneously, so that the parameters of each single equation also take the information provided by the other equations into consideration. The result has greater efficiency of the parameter estimates because additional information is used to describe the system. This efficiency gains increase with increasing correlation among the error terms of different equations (Judge et al. 1998, Yahya et al. 2008).

The present study focuses on determining possible factors responsible for military coups in the ECOWAS countries. The study considers four countries (Burkina Faso, Guinea, Mali and Niger) that have experienced military coups and four other countries (Cote d’Ivoire, Ghana, Nigeria and Togo) that have not had military coups between 1991 and 2014. The SUR model will estimate simultaneously the parameters of all the equations of the countries that experienced military coups and those that have not while correlation among the cross-sectional countries is taken into consideration. We have stated earlier that ECOWAS countries are related, hence the correlation of their error terms.

An N- seemingly unrelated regression system equations can be represented in matrix form as thus:

(11) Y 1 = X 1 β 1 + ε 1   Y 2 = X 2 β 2 + ε 2 Y 3 = X 3 β 3 + ε 3 Y 4 = X 4 β 4 + ε 4 Y N = X N β N + ε N

The system of N-equations can be written in a clearly vector notation as:

(12) Y i = X i β i + ε i where i = 1 , 2 , … , N

Where Y i denotes the M × 1 column vector of ith dependent variable. X i symbolizes the M × K matrix of observations for the K-1 exogenous variable and a column vector of 1’s for the ith equation. β i is the K × 1 column vector parameters for the ith equations. ε i implies the M × 1 column vector of the disturbance error term for the ith equations.

The system of M-equations can be turned into a single equation, usually estimated by vertically stacking the vectors and matrices as follows:

(13) Y 1 Y 2 Y 3 . . . Y N = X 1   0   0   . . .   0 0   X 2   0   . . .   0 0   0   X 3     . . .   0 . . .   . . .   . . .   . . .   0 0   0   0   . . .   X N   β 1 β 2 β 3 . . . β N + ε 1 ε 2 ε 3 . . . ε N

The single compact equation from the stacked model can be written as:

(14) Y = X β + ε

Where y is an (M·N) × 1 column vector observations on the dependent variables for the N-equation. While Xisan(M·N) × (M·K) matrix of observation on the endogenous variables. βisan(M·K) × 1 column vector of parameters for the M-equations, and εisan(M·N) × 1 column vector of error terms for the N equations.

6 Summary Statistics

6.1 Pretest

The authors applied two standard unit root tests prominent in panel analysis, namely: The Breitung unit root (2000) and the Levin, Lin, and Chu unit root test (2002). The Null hypothesis (Ho) for the test states that there is a unit root with a common process across all countries under review. The variables are subjected to a panel unit test to ascertain the stationarity of the variables. From the result, both tests show that the variables are stationary at the level.

7 Results Presentation

The empirical method employed in the study is the pooled fixed effect and Seemingly Unrelated Regression models developed by Zellner (1962). The aggregate estimates of the countries with military coups and countries without military coups in ECOWAS using Pool Fixed Effect are presented in Table 1. System equations that reveal independent estimates of each country with a military coup in ECOWAS using Seemingly Unrelated Regression are presented in Tables 2 and 3.

Table 1:

Unit root test.

Variables Breitung unit root Levin, Lin, and Chu unit root
GDPC −1.7691ba −0.6177ba
CAPF −3.3948ba −0.2580ba
INF −0.5216aa −1.5529ba
MEX −0.1699aa −3.4992aa
TOPNX −2.1284ba −7.4582ba
UPM −0.0985ba −0.9.2947ba
PISB −1.4721ba −1.6432ba

  1. a, and brepresent significance at the 1 %, and 5 % levels respectively, while a implies stationarity at the level.

Table 2:

Pool fixed effect result of determinants of political instability in ECOWAS.

Exogenous variables Countries with military COUPd Countries without COUPSe
GDPC −0.0064a (0.0050) −0.000452a (0.0005)
CAPF −0.0428 (0.4609) 0.01009 (0.3303)
MEX −0.05923a (0.0000) −0.15547a (0.0005)
INF 0.01696 (0.1298) 0.01934a (0.0027)
TOPNX 3.13065a (0.0050) −2.0696 (0.3817)
UPM 0.0294a (0.0236) −0.16433a (0.0028)
Constant 0.6207 (0.0021) 0.3970 (0.4266)
Observations 128 128
R2 0.8136 0.7503

  1. p-value is in parentheses. a. b, and cdenote 1, 5 and 10 percent significance, respectively. dBurkina Faso, Guinea, Mali and Niger. eCote d’Ivore, Ghana, Nigeria and Togo.

Table 3:

Seemingly unrelated regression estimates (SUR) of determinants of political instability in the ECOWAS region with military COUP.

PISBBF PISBGN PISBML PISBNG
GDPC −0.0675b (0.0002) −0.0028b (0.025) −0.0019b (0.0003) −0.041b8 (0.0018)
CAPF 0.07651 (0.6841) 0.02507 (0.3500) −0.0146 (0.0169) −0.061a (0.0009)
MEX −0.19668b (0.0053) 0.04346 (−0.3489) 0.0182b (0.0001) −0.0450b (0.0056)
INF −0.2018 (0.4189) −00128 (0.6744) −0.00165 (0.9147) 0.0208b (0.089)
TOPNX 0.0925b (0.0005) 0.0929b (0.0439) 0.6257b (0.0016) −1.3264 (0.7320)
UPM −0.2699 (0.4521) −0.0455 (0.8969) 0.3880b (0.0324) 0.1953b (0.0668)
Constant 1.7176b (0.0002) 0.1767b (0.0001) 0.14648b (0.0001) 0.0710b (0.0008)
Observations 32 32 32 32
R2 0.563 0.6408 0.8016 0.6559

  1. p-value is in parentheses. a. b, and cdenote 1, 5 and 10 percent significance, respectively.

7.1 Discussions on Countries with Military Coups in ECOWAS

Table 1 reveals that the GDP per capita (GDPC) has an inverse relationship with political instability in the ECOWAS region. A percentage fall in GDPC increased political instability by 0.0064 %. This implies that GDPC (poverty) and a reduction in citizens’ welfare triggers political instability in the region. Observably, an increase in unemployment (UPM) by 1 % stimulates political instability by 0.020 %. Military expenditure (MEX) is inversely related to military coups in ECOWAS states that have experienced coups in this study. Table 1 also indicates that 1 % reduction in military expenditure could result in a 0.05 % possibility of triggering political instability in the ECOWAS states. Foreign interference, which is proxied by trade openness (TOPNX), is significant and positively related to military coups in the ECOWAS region. The TOPNX-indicator suggests that entanglement with foreign actors/countries influenced political instability in the ECOWAS. One common factor across the countries that experienced democratic reversal in the ECOWAS region considered in this study is that they were colonised by the French. The estimates show that GDPC, MEX, TOPNX, and UPM are important drivers of political instability in the region. This could be explained given the fact that most of the ECOWAS states are endowed with one mineral deposit or the other. For example, Burkina Faso has gold and diamond deposits; Mali has gold and Zinc, Niger is known for Gold and manganese, and Guinea is an exporter of Bauxite and iron ore. One common feature of the ECOWAS region is that these minerals are either untapped or tapped by non-state actors, or they are tapped and exported overseas without value addition. The region earned little foreign exchange from the mineral resources and spent huge amounts of money on importing finished goods from abroad. This negatively affects GDP. Low GDP negatively impacts investment and unemployment, and worsens GDPC. Inflation and capital formation (CAPF) are silent in the model. Table 1 indicates that Capital Formation (CAPF) does not exert any influence on the region. The empirical result from the pool data found that democratic reversal in the ECOWAS region is triggered by a reduction in the welfare of the citizens, denoted by GDPC, Military/security funding (MEX), exposure to external influence (TOPNX) and unemployment (UPM).

7.2 Discussions of ECOWAS Countries without Military Coup During the Period Under Consideration

The analysis includes an examination of four additional countries from the ECOWAS region that did not experience democratic reversal during the study period. The choice of the four countries helped to compare the impact of exogenous variables on the selected ECOWAS countries that have not experienced military coups. The results reveal that GDPC is significant and inversely related to political instability. MEX and UPM are significant and indirectly related to political instability. The results suggest that when MEX and UPM decrease by 1 %, it is likely to influence political instability by about 0.15 and 0.16 % respectively. Inflation also contributes to instability in the region. A percentage rise in inflation leads to about 0.01 % in contributing to political instability in these economies. Conclusively, these countries are susceptible to political instability (coups) like their ECOWAS counterparts (the ones that experienced coups) given that most of the indicators have a similar influence in both groups.

Further, these four countries without military coups, when compared with the other four countries, are relatively politically stable. A critical look at Nigeria reveals that since the start of the fourth republic, Nigeria has successfully conducted elections and ensured the transfer of power from one administration to the other, despite the many challenges such as terrorism, kidnapping, and corruption facing the polity. The country’s GDP and military expenditure remain among the highest in the ECOWAS region and Africa as a whole. On its part, Ghana has been a beacon of democracy in the region. Just like Nigeria, there has been a smooth conduct of elections regulating the change of government in the country. In 2024, Ghana witnessed a successful conduct of elections, which saw Ghanaians voting to return former president John Mahama to office. This peaceful transfer of power became commendable based on democratic backslides in the ECOWAS region. Similarly, Côte d’Ivoire and Togo have held elections despite the many problems they face.

Table 3 shows the simultaneous estimates of four independent models of the countries with military coups in ECOWAS. The estimates are presented in four variants for the four countries. Specifically, models PISB BF , PISB GN , PISB ML , and PISB NG report the estimates of Burkina Faso, Guinea, Mali and Niger, respectively, using the SUR model. The rationale for estimating the four independent equations simultaneously is such that each equation takes the information provided by the other equations into account. One of the arguments against the pool data technique is that its estimates may not unmask the true response of the political instability to the control variables due to aggregation problems. Furthermore, different countries have different structures, and these structures determine how exogenous variable influences governance institutions. GDPC, MEX. TOPNX, CAPF, UPM, and PISB are available in the ECOWAS region. Their error terms may be correlated, as is expected in cross-sectional regression. Moreover, the ECOWAS protocol involves the unification of currency, the free movement of people and goods, etc. This implies that error terms are likely to be contemporaneously correlated. Hence, pooled OLS estimates will be biased in such a study. For us to independently estimate the various ECOWAS countries and account for the weakness of OLS. The study adopted the Seemingly Unrelated Regression (SUR) estimation technique. This technique helps to compare the result of the pool effect estimates and that of the individual/independent countries.

7.3 POST-TEST Result (Multicollinearity)

Table 4 reveals the behaviour of the variables across the country under review when subjected to the multicollinearity test. Glaringly, multicollinearity is a major problem in an econometric analysis, especially in a panel analysis like ours. The result shows that there is no collinearity within the heterogeneous countries under review. This is evidenced by the result in Table 4 because the pair-wise correlations are quite small and less than 0.5. The inference states that collinearity exists if the pair-wise correlation values are more than 0.5. Therefore, we conclude that there is no collinearity across the countries. The result gives credence and validity to the application of SUR estimation as an Unbiased technique as used in the analysis.

Table 4:

Correlation matrix of residuals.

PISBBF PISBBF PISBGN PISBML PISBNG
PISBBF 1.000000
PISBGN 0.468781 1.000000
PISBML 0.271534 0.380041 1.000000
PISBNG 0.007385 0.048658 0.023753 1.000000

8 Discussion of the SUR Results (Table 3)

8.1 Political Instability Burkina Faso (PISBBF)

The result in Table 2 indicates that GDPC exerted a negative and significant influence on PISBBF in Burkina Faso. As GDP per Capita decreased by 1 %, political instability increased by 0.06 % on average. This implies that a reduction in GDPC stimulates instability in Burkina Faso. This buttresses why the GDPC of Burkina Faso was very low, considering the data from the stylised fact. The result reveals that CAPF and unemployment are silent in Burkina Faso. The insignificance of Capital formation implies a low investment rate, which gives rise to increased unemployment. Hence, unemployment was also silent in the model. The channel will lead to widespread poverty in the country. Persistent poverty is likely to create unrest among the people vis-à-vis democratic reversal. Political instability throughout 1991–2022 increased at an annual rate of 0.09 % resulting from a percentage rise in trade openness. Burkina Faso is rich in mineral resources such as gold, zinc, diamonds, limestone, etc. These resources have attracted non-state actors and foreign interest into the country. Some elites and politicians have connived with foreigners in mining these resources to the disadvantage of the general citizens. More so, the spread of inequality is higher than in other countries in this study. Data observed reveals that the income share held by the highest 20 % of the population is more than 10 % of the GDP. The country has witnessed a resource curse phenomenon. This phenomenon can trigger anger in the citizens and, as such, leads to democratic reversal. This is the rationale why the increase in trade openness is positive and significant to political instability in Burkina Faso. Military welfare (MEX) is negatively related to political instability in Burkina Faso. A 1 % fall in military expenditure, on average, enhances political instability by 0.07 %. This can be explained given the fact that Burkina Faso’s GDPC, investment, and output growth are low, which will retard government expenditure vis-à-vis military expenditure (welfare) and could directly lead to a military coup in the country.

8.2 Political Instability in Guinea (PISBBF)

An assessment of the impact of GDPC on democratic reversal in Guinea was found to be inversely related. This relationship follows the apriori expectation. When citizens’ welfare (income) increases, they are less likely to be involved in protests or riots and vice versa. Estimates of GDPC suggest that a 1 % decrease in Guinean GDPC, on average, led to a 0.002 % chance of triggering political instability in the country. This is evidenced as the country recorded the highest number of maternal mortalities across the country considered in the study, with a ratio of 455 persons per 100,000 live births. TOPNX is significant and positively influenced the democratic reversal in Guinea. A percentage rise in TOPNX deteriorates Guinean political instability by 0.09 %. This could be explained using the resource curse theory. Guinea’s foreign exchange earning comes from Bauxite and Iron ore. These minerals are explored, mined, and exported as raw materials to foreign countries, while it is imported at exorbitant prices as finished products inform of vehicles, and appliances like refrigerators, washing machines, etc. This pattern of trade depletes the Guinean economy and could create an uprising in the country. Inflation, unemployment, military expenditure, and capital formation did not produce any significant results in democratic reversals from the study.

8.3 Political Instability in Mali (PISBML)

GDPC has implications for democratic reversal in Mali. According to the Malian regression estimate, the reduction of GDPC by 1 % contributes to 0.0019 % of democratic reversal in Mali. An important trigger of economic instability in Mali is unemployment. An average percentage increase in unemployment worsened political instability by about 0.38 %. Trade openness (TOPNXML) is significant and positively influenced democratic reversal in Mali. Going by the apriori, TOPNX is expected to have an inverse relationship with political instability, but the reverse is the case. This behaviour could be explained by the high external debt in Mali. The observed data shows that Mali’s external debt is about 57.3 % percent of the Gross National Income. It could be that the foreign exchange realised from the export of gold and limestone is used in servicing debt. This explains why capital formation is not significant and GDPC contributes to worsening political instability in the model. It seems that Income generated from foreign exports and domestic savings is not channelled into productive sectors and the creation of jobs. Unemployment exhibits a positive impact on democratic reversal. The estimate suggests that Political instability worsens by 0.38 % if unemployment rises by 1 %. MEX explains the military coup in Mali as shown in the result. The positive relationship may arise from the unsatisfactory disposition of the military on how the Malian economy is coordinated. There is high poverty, unemployment, external debt, and a generally low standard of living, especially when considering the benefits of the natural resources’ endowments in the country.

8.4 Political Instability in Niger (PISBNG)

The estimates of (PISBNG) model indicate that GDPC, CAPF, and MEX are significant and negatively influence political instability in Niger. A % reduction in GDPC increased political instability by 0.04 %. When military expenditure increased by 1 %, the likelihood of a military coup will decrease by 0.045 % on average. Unemployment and inflation follow the a priori expectation of being positively related to the military coup in Niger. Military coups will be exacerbated by 0.19 % and 0.02 % if unemployment and inflation rise by 1 % respectively.

8.4.1 A Summary of Findings of Countries with Military Coups in ECOWAS

A summary table/synthesis of results.

Determinants of political instability Findings Causes
GDPC (poverty) A percentage fall in GDPC increased political instability. A reduction in citizens’ welfare triggers political instability in the region Earning little from exporting due to low value addition on goods exported, & French colonisation
Unemployment (UPM) An increase in unemployment (UPM) by 1 % stimulates political instability by about 0.02 % Lack of productive sectors, lack of industrialisation and low levels of job creation
Military expenditure (MEX) 1 % reduction in military expenditure could result in a 0.05 % possibility of triggering political instability in the ECOWAS states Corruption, politics
Trade openness (TOPNX), The TOPNX-indicator suggests that entanglement with foreign actors/countries influenced political instability in the ECOWAS Entanglement with foreign actors

  1. Source: Authors Compilation (2025).

9 Discussions of the Findings

The analysis of the determinants of political instability in the ECOWAS sub-region shows that the major determinants of political instability in the sub-region are GDP per Capita, military expenditure, and trade openness. From 1991 to 2022, the analysis shows that both in states that have experienced military coups (Burkina Faso, Guinea, Mali and Niger) and in states that have not had military coups (Cote d’Ivoire, Ghana, Nigeria and Togo), political instability is influenced and caused by poor socio-economic conditions of the society. In most of the ECOWAS states under study, military expenditure has been poor over the years, making the military ineffective in protecting the state from aggression. For example, since the start of the twenty-first century, there have been three successful military coups[11] in Niger. The first was in 1999, the second in 2010 and the third in 2023. These coups have been carried out with ease by the military in Niger. When compared with other countries in Africa and the ECOWS subregion, Niger ranks one of the lowest in military expenditure. According to Global Fire Power (2024), Niger ranks 127 out of 145 countries on defence budget ($ 250,000.000) in 2024, which is a far cry from other countries in the region with high military expenditure. Similarly, just like Niger, Mali has a low and poor military expenditure, and this has contributed to the political instability in the country. The country’s military expenditure has not been stable since its independence from France. From 1970 to 2010, Mali’s military expenditure was at its lowest, with budgets under $200 million (Stockholm International Peace Research Institute 2024). This illustrates why there have been successful and unsuccessful military coups in Mali since the start of the twentieth century. Since 2000, the percentage of military expenditure of the general government expenditure has been low. Before the 2012 Malian Coup detat, the percentage of the military expenditure to the general government expenditure in Mail stood at 7.6 % in 2000, 7.1 % in 2001, 6.4 % in 2002, 6.8 % in 2003, 6.5 % in 2004, 6.4 % in 2005, 6.3 %, in 2006, 6.3 %, in 2007, 7.7 % in 2008, 6.2 % in 2009, 6.8 % in 2010, and 6 % in 2011 (World Bank Group Data 2024). Since the military coup in 2012, there have been two other coups in 2020 and 2021. The low military expenditure in the country necessitated successful military coups in the country. This thought was highlighted in ReliefWeb’s 2012 article on the military coup in Mali. In their words:

…the morale within the army was seriously affected by consecutive defeats recorded over the past few weeks. Soldiers complained of the lack of adequate means and resources to fight the Tuareg insurgents. They saw in the soft attitude of the government a recipe for disaster and national humiliation…the option of choosing political dialogue over military confrontation is rooted in the financial and economic difficulties facing Mali, with repercussions on its security forces… the reduction in the national defence budget and investments in socio-economic programme to improve the general living conditions of the citizens including health, education and infrastructure development (Reliefweb 2012).

Similarly, Alozieuwa (2013:387) stated that the sorry state of the Malian military appeared to prevail in an atmosphere of distrust of the military by political leaders.

In Burkina Faso, the military coup in 2022 was also aided by the previous government’s low expenditure and financing. Since 1991, the military expenditure % of the total government expenditure has been very low when compared to countries without recent political instability in the ECOWAS sub-region, knowing that the military budget is low. From 1995 to 2017, the military expenditure % of the total government expenditure has been between 6.5 % (1995) to 5.2 % (2017) (World Bank Group 2024), which is poor, exposing the state to internal and external aggression. In 2022, the military expenditure % of the total government expenditure in Burkina Faso stood at 12.4 %, with a budget of 562,583,349.2 USD, unlike Nigeria, where the budget for the military in 2021 was 1.78 trillion USD and 1.32 trillion USD in 2022.

Just like in Mali, Niger and Burkina Faso, Guinea, the military coup that occurred in the country could be traced to low military expenditure. In 2021, the military expenditure % of the total government expenditure in Guinea stood at 10 % in 2020, 8.6 % (World Bank collection of development indicators, 2022). Despite the political instability that occurred in Guinea in 2021, Guinea remains the country with the highest military expenditure when compared with the other countries that experienced a military coup in the ECOWAS subregion. In 2022, the total military expenditure for Guinea was 3.89 % trillion. The statistics from these countries has shown that low and poor military expenditure leads to military coup and political instability. This finding is in line with scholars like Blomberg (1996) and Balan (2015), which argues that an increase in defence and military expenditure is found to decrease political instability.

The findings also show that trade openness was a major determinant of political instability. The four countries that have experienced a military coup or political instability in the country mostly depend on imports while exporting little or nothing abroad. This imbalance is limiting the growth of their economy as they are disadvantaged in the global trading system because good trade openness has a positive effect on economic growth both in the short and long run (Keho and Grace Wang 2017). For example, in Niger, the World Bank trade openness figure for 2023 stood at 30.42 % which was the lowest in recent times, representing a decline from 31.33 percent in 2022 (Theglobaleconomy 2024). Similarly, in a study on trade openness in the Niger Republic from 1980 to 2013, Aboubacar et al. (2014) noted that trade openness has been efficient to spur economic growth in Niger throughout the study due to the government’s development of some infrastructures during the uranium boom period of the 1970s and early 1980s. But this changed as a result of the corrupt and bad government in Niger Republic. Insecurity, poverty and political instability in Niger have constituted big obstacles for the welfare of trade activities in the country thus limiting the goals of trade openness in the country. In Burkina Faso, the problem associated with trade openness in the country has resulted from internal and external crises and the actions of radical groups in the Sahel.

Poor GDP per Capita is a contributory factor to political instability in Burkina Faso, Guinea, Mali and Niger. In most of these countries, the standard of living is low and poor, thus enabling political instability and military coups. During the years under study, these countries account for the lowest GDP per Capita in Africa, significantly contributing to political instability in the sub-region. From 1991 to 2022, the GDP per Capita for Mali fluctuated between $298.6 (1991) -$831.2(2022) and when this is compared with stable democracies in the ECOWAS sub-region, it is quite low and alarming. For Guinea, it fluctuated between $664.5 -$1.515.2, for Burkina Faso, it fluctuated between $334.8 -$830, for the Niger Republic $380.5-$588.9 (World Bank Group 2024). These figures illustrate that the country’s welfare, standard of living and quality of life over the years determine political instability. For instance, in the Niger Republic, the military coup in the country was celebrated by the people based on the inability of the government to adequately cater for the populace. According to Yabi (2023), the living conditions for many in Niger remain dire, which is a result of the way the country was governed over the years. When compared with other GDP per Capita in other stable democracies in the ECOWAS sub-region, it is seen that those countries have relatively higher GDP per Capita. In Ghana, according to the World Bank Group 2024, the GDP per Capita has fluctuated between $416.8 (1991) -$2.218.4(2022), which is remarkably high for the ECOWAS sub-region. In Nigeria, the GDP per Capita has fluctuated between $609.4 (1991)- $2.162.6(2022). These two countries have shown that a good and impressive GDP per Capita limits political instability.

10 Conclusion

Governments in the ECOWAS sub-regions have an important role to play in preventing political instability in the sub-region. This is because it is deduced that the conditions of those societies influence the increasing wave of political instability in the ECOWAS subregion. Most countries that have experienced military coups and political instability in the ECOWAS subregion have poor economies, poor military expenditures, low GDP per Capita, and poor trade openness police. Even countries like Nigeria and Ghana are susceptible to political instability based on the current problems witnessed in their polity.

11 Recommendations

Recommendations for strengthening political stability in ECOWAS.

Empirical findings from this study emphasise that material conditions, notably GDP per capita, military expenditure, trade openness, and unemployment, are primary drivers of political instability in ECOWAS countries. To address these challenges effectively, ECOWAS member states and their international partners should undertake targeted, system-wide reforms in the economic, security, and governance sectors. Some of these reforms should focus on:

  1. Strengthening Economic Resilience through Livelihood Support in the Sub-region. This can be achieved through economic growth and poverty reduction via targeted investments in agriculture, small and medium enterprises (SMEs), and infrastructure.

  2. Upgrading Security Sector Capacities. This upgrade can involve increasing member state military budgets in line with GDP growth, strengthening institutional capacity without creating dominant political factions. Additionally, regional military and police intelligence cooperation should be expanded to effectively address transnational threats.

  3. Enhancing Democratic Norms and Preventing Constitutional Manipulation: The Supplementary Protocol on Democracy & Good Governance should be amended to explicitly prohibit attempts to manipulate constitutions or extend terms. Furthermore, ECOWAS itself should initiate and establish automatic monitoring systems for economic and political benchmarks, including GDP, unemployment, and inflation, to provide early political warning indicators.

  4. Collaborative Governance and Institutional Reform: ECOWAS institutions, such as the Community Court of Justice and the Commission, should be empowered to investigate governance breaches and sanction high-level misconduct.

Implementing this multi-pronged strategy can aid states in ECOWAS and its partners in tackling the economic, security, and governance failings revealed in this study, breaking the cycle of instability and reinforcing democratic institutions across West Africa.

Corresponding author: Richard Uzoma Gbemudia, Research Department, Nigerian Institute of International Affairs (NIIA), Lagos, Nigeria, E-mail:

References

Aboubacar, B., D. Xu, and A. M. Ousseini. 2014. “Does Trade Openness Matter for Economic Growth in Niger?” Theoretical Economics Letters 4 (9): 916–27. https://doi.org/10.4236/tel.2014.49115.Search in Google Scholar

Abu, N., and M. Z. A. Karim. 2015. “The Causal Relationships Among Corruption, Political Instability, Economic Development and Foreign Aid: Evidence From The Economic Community of West African States.” Journal of Applied Economic Sciences 10 (1): 20–33, https://doi.org/10.5709/ce.1897-9254.159.Search in Google Scholar

Abu, N., M. Z. A. Karim, and M. I. A. Aziz. 2014. “Corruption, Political Instability and Economic Development in the Economic Community of West African States (ECOWAS): Is there a Causal Relationship?” Contemporary Economics 9 (1): 45–60. https://doi.org/10.5709/ce.1897-9254.159.Search in Google Scholar

Ajala, O. 2023. Understanding the Crisis of Democracy in West Africa and the Sahel. Geneva Centre for Security Policy. https://www.gcsp.ch/publications/understanding-crisis-democracy-west-africa-and-sahel (accessed April 24, 2024).Search in Google Scholar

Akinyemi, O., D. O. Apeloko, G. U. Osimen, and C. E. Chukwudi. 2024. “The Economic Community of West African States (ECOWAS) and the Resurgence of Military Coups in West Africa.” Journal of African Union Studies 13 (2). https://doi.org/10.31920/2050-4306/2024/13n2a4.Search in Google Scholar

Alesina, A., S. Özler, N. Roubini, and P. Swagel. 1996. “Political Instability and Economic Growth.” Journal of Economic Growth 1 (2): 189–211.10.1007/BF00138862Search in Google Scholar

Al-Jabri, N., N. Cambell, S. Saha, and S. Khan. 2022. “The Role of Youth Bulge on Political Instability: Cross-Country Evidence.” Economic Analysis and Policy 76: 1053–74. https://doi.org/10.1016/j.eap.2022.09.013.Search in Google Scholar

Alozieuwa, S. H. O. 2013. “The March 22, 2012 Coup in Mali: Lessons and Implications for Democracy in the West Africa Subregion in the Wave of Transnational Terrorism.” Democracy and Security 9 (4): 383–97. https://doi.org/10.1080/17419166.2013.833811. https://www.jstor.org/stable/48602751.Search in Google Scholar

Armed Conflict Location & Event Data Project. “2023. Political Violence and the 2023 Nigerian Election.” https://acleddata.com/2023/02/22/political-violence-and-the-2023-nigerian-election/ (accessed June 6, 2024).Search in Google Scholar

Balan, F. 2015. “The Nexus Between Political Instability, Defense Spending and Economic Growth in the Middle East Countries: Bootstrap Panel Granger Causality Analysis.” Economic Insights – Trends and Challenges IV (LXVII): 1–14.Search in Google Scholar

Blomberg, S. B. 1996. “Growth, Political Instability, and the Defence Burden.” Economica 63 (252): 649–72. https://doi.org/10.2307/2555001 Search in Google Scholar

Chigozie, C. F., and P. T. Oyinmiebi. 2022. “Resurgence of Military Coups in West Africa: Implications for ECOWAS.” African Journal of Social Sciences and Humanities Research 5 (2): 52–64. https://doi.org/10.52589/ajsshr-w9f5vaxe.Search in Google Scholar

Fafore, O. A. 2019. “Radical Islam and Transnational Security in West Africa.” Journal of African Union Studies 8 (2): 103–18. https://doi.org/10.31920/2050-4306/2019/8n2a6. https://www.jstor.org/stable/26890406.Search in Google Scholar

Gbemudia, R. U., D. Godwin, and U. H. Ologe. 2025. “From Conception to Practice: the Theoretical and Philosophical Foundations of Silencing the Guns.” In Silencing the Guns, Vol. 2, edited by N. I. Erameh, N. B. Breakfast, and E. N. Ubi. Singapore: Palgrave Macmillan. https://doi.org/10.1007/978-981-96-7159-5_2.Search in Google Scholar

Gbemudia, R., and D. Teneng Cho. 2024. “The Cameroon Anglophone Crisis and the Responsibility to Protect.” In Civilian Protection and the Anatomy of the Responsibility to Protect Doctrine in the 21st Century (Book Project), edited by N. I. Erameh, and V. Ojakorotu. Palgrave Macmillan.10.1007/978-981-99-8163-2_8Search in Google Scholar

Globalfirepower. 2024. “Defense Budget by Country.” (accessed October 2, 2024). https://www.globalfirepower.com/defense-spending-budget.php Search in Google Scholar

International World Integrated Trade Solution. 2024. Trade Indicators, Merchandise Trade. (Sundry Products Export and Import to Sub-Saharan Africa from the ECOWAS). https://wits.worldbank.org/country-indicator.aspx?lang=en (accessed June 15, 2024).Search in Google Scholar

Jannils, L. 2021. “The Concept of Political Instability in Economic Research.” International Journal of Management and Economics 57 (3): 268–84, https://doi.org/10.2478/ijme-2021-0016.Search in Google Scholar

Jong-A-Pin, R. 2009. “On the Measurement of Political Instability and its Impact on Economic Growth.” European Journal of Political Economy 25 (1): 15–29.10.1016/j.ejpoleco.2008.09.010Search in Google Scholar

Judge, G. G., W. E. Grifftths, R. C. Hill, H. Lutkepohl, and T. C. Lee. 1998. Introduction to the Theory and Practice of Econometrics, 2nd ed. New York: Wiley.Search in Google Scholar

Keho, Y., and M. Grace Wang. 2017. “The Impact of Trade Openness on Economic Growth: the Case of Cote d’ivoire.” Cogent Economics & Finance 5 (1). https://doi.org/10.1080/23322039.2017.1332820.Search in Google Scholar

Marc, A., N. Verjee, and S. Mogaka. 2015. The Challenge of Stability and Security in West Africa. Africa Development Forum. World Bank; and Agence Française de Développement. https://hdl.handle.net/10986/22033License:CCBY3.0IGO.10.1596/978-1-4648-0464-9Search in Google Scholar

Mbaku, J. M. 1988. “Political Instability and Economic Development in Sub-saharan Africa: Some Recent Evidence.” The Review of Black Political Economy 17 (1): 89–111, https://doi.org/10.1007/BF02900956.Search in Google Scholar

Mhaka, T. 2023. “ECOWAS is Undoubtedly in Trouble, but it Still Has Potential.” https://www.aljazeera.com/opinions/2023/9/27/ecowas-is-undoubtedly-in-trouble-but-it-still-has-potential (accessed June 6, 2024).Search in Google Scholar

Morrison, D. G., and H. M. Stevenson. 1971. “Political Instability in Independent Black Africa: More Dimensions of Conflict Behavior within Nations.” Journal of Conflict Resolution 15 (31): 347–68, https://doi.org/10.1177/002200277101500306.Search in Google Scholar

Obinna, G. S., and O. C. Semudara. 2024. “Resurgence of Coup D’état in Africa in an Era of Mass Democratisation: A Study of Niger, Burkina Faso, and Mali Experiences.” African Journal of Law, Political Research and Administration 7 (4): 49–62.10.52589/AJLPRA-48OTNSBTSearch in Google Scholar

Obisie-Orlu, V. 2022. “A Snapshot of the Roots of Instability in West Africa.” https://gga.org/a-snapshot-of-the-roots-of-governance-instability-in-west-africa/ (accessed June 20, 2024).Search in Google Scholar

Okafor, J. C., and U. C. Okafor. 2015. “ECOWAS and Democratic Reversal in West Africa: Re-Visiting Military Incursion on the State Leadership.” International Affairs and Global Strategy, 37 (2015): 120–8.Search in Google Scholar

Ojo, O. J. 2023. “The Rising Coups and Democratic Consolidation in Francophone West Africa: A study of Mali, Guinea, and Burkina Faso.” Doctoral diss., University of Lagos.Search in Google Scholar

Orji, A., S. U. Akachukwu, and E. A. amd Ilori. 2014. “Foreign Capital Inflows and Growth: an Empirical Analysis of WAMZ Experience.” International Journal of Economics and Financial Issues 4 (4): 971–83.Search in Google Scholar

Reliefweb. 2012. “Mali’s Unfortunate Military Coup an Unnecessary Setback for Democracy.” https://reliefweb.int/report/mali/mali%E2%80%99s-unfortunate-military-coup-unnecessary-setback-democracy (accessed October 2, 2024).Search in Google Scholar

Sowale, A. O. 2024. “The Military Coup in Niger Republic: Anti-democracy or Pro-autocracy, and Ominous Conflict Trend Implications for Nigeria in West Africa.” Africa Review 17 (1): 68–90.10.1163/09744061-bja10172Search in Google Scholar

Stockholm International Peace Research Institute. 2024. – with minor processing by Our World in Data. “Military expenditure” [dataset]. Stockholm International Peace Research Institute, “SIPRI Military Expenditure Database” [original data]. https://ourworldindata.org/grapher/military-spending-sipri (accessed October 4, 2024).Search in Google Scholar

Theglobaleconomy. 2024. Niger: Trade Openness. https://www.theglobaleconomy.com/Niger/trade_openness/ (accessed January 12, 2025).Search in Google Scholar

World Bank Group. 2024. https://data.worldbank.org/indicator/MS.MIL.XPND.ZS?locations=ML (accessed October 4, 2024).Search in Google Scholar

World Bank Group. 2024. Indicators: Economy and Growth. https://data.worldbank.org/indicator/NY.GDP.PCAP.CD?view=excel. https://data.worldbank.org/indicator?_gl=1*w1a0qp*_gcl_au*MTk4MzQ1MTcxNC4xNzI0NjE5MDYz (accessed June 15, 2024).Search in Google Scholar

World Bank Group Data. 2024. “Military Expenditure (% of the General Government Expenditure) Burkina Faso.” https://data.worldbank.org/indicator/MS.MIL.XPND.ZS?locations=BF&view=chart (accessed October 2, 2024).Search in Google Scholar

Yabi, Gilles. 2023. “The Niger Coup’s Outsized Global Impact.” Carnegie Endowment for International Peace. https://carnegieendowment.org/posts/2023/08/the-niger-coups-outsized-global-impact?lang=en (accessed August 31, 2023).Search in Google Scholar

Yahya, W. B., S. B. Adebayo, E. T. Jolayemi, B. A. Oyejola, and O. O. M. Sanni. 2008. “Effects of Nonorthogonality on the Efficiency of Seemingly Unrelated Regression (SUR) Models.” InterStat Journal 1: 1–29.Search in Google Scholar

Zellner, A. 1962. “An Efficient Method of Estimating Seemingly Unrelated Regression Equations and Tests for Aggregation Bias.” Journal of the American Statistical Association 57 (298): 348–68.10.1080/01621459.1962.10480664Search in Google Scholar

Zellner, A., and D. S. Huang. 1962. “Further Properties of Efficient Estimators for Seemingly Unrelated Regression Equations.” International Economic Review 3 (3): 300–13, https://doi.org/10.2307/2525396.Search in Google Scholar
Received: 2024-11-07
Accepted: 2025-09-30
Published Online: 2025-10-20
Published in Print: 2025-11-25

© 2025 the author(s), published by De Gruyter, Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 International License.

Articles in the same Issue

  1. Frontmatter
  2. Editors Note
  3. Editors’ Note
  4. Special Issue: Emotional Dynamics of Politics and Policymaking; Guest Editors: Georg Wenzelburger and Beatriz Carbone
  5. Bringing Emotions into the Study of Responsiveness: The Case of Protective Policies
  6. Emotional Reactions to Protective Policies on the Political Spectrum
  7. Regular Articles
  8. Determinants of Political Instability in ECOWAS (1991–2022)
  9. The Impact of International Remittances on Public Debt Sustainability in Kerala: Evidence from the FMOLS Approach
  10. Bayesian Analysis of Tuberculosis Cases in Bolgatanga Municipality, Ghana–West Africa
https://doi.org/10.1515/spp-2024-0056
Keywords for this article
ECOWAS; political instability; military expenditure; GDP per capita; military intervention
Creative Commons
BY 4.0

Articles in the same Issue

  1. Frontmatter
  2. Editors Note
  3. Editors’ Note
  4. Special Issue: Emotional Dynamics of Politics and Policymaking; Guest Editors: Georg Wenzelburger and Beatriz Carbone
  5. Bringing Emotions into the Study of Responsiveness: The Case of Protective Policies
  6. Emotional Reactions to Protective Policies on the Political Spectrum
  7. Regular Articles
  8. Determinants of Political Instability in ECOWAS (1991–2022)
  9. The Impact of International Remittances on Public Debt Sustainability in Kerala: Evidence from the FMOLS Approach
  10. Bayesian Analysis of Tuberculosis Cases in Bolgatanga Municipality, Ghana–West Africa
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