West Africa represents a very good case of a sub-region currently plagued with the problem of food insecurity. Traditional theories have attributed the increasing food insecurity in the region to problems of poor governance, corruption and climate change. In view of the persistent and increasing nature of armed conflict in the sub-region, the purpose of this paper is to examine the effect of increasing armed conflict on food security in Economic Community of West African States (ECOWAS) member countries.
The study utilized the dynamic generalized method of moments (GMM) to investigate the effect of conflict intensity on food security in the 14 member states of the ECOWAS using annualized panel data from 2005 to 2015.
The findings reveal that armed conflict is a significant predictor of food security in West Africa.
The findings of the study bring to fore, the urgent need to rethink global initiative for combating food insecurity. The effort must also identify the causes of armed conflicts and design sound strategies for de-escalating the armed conflicts. Resolving the escalating armed conflict entails developing a conflict resolution framework that is extremely sensitive to the causes of conflict in Africa and adopting localized ex ante institutional diagnostics that would help in understanding the nature of the conflicts.
Traditional theory perceives climate change, social injustices, property right, food insecurity, religious extremism and bad governance as the predictors of armed conflicts. In this study, the authors departed from the traditional theory by demonstrating that the nature and trend of armed conflict could also pose a serious threat to food security.
Ujunwa, A., Okoyeuzu, C. and Kalu, E.U. (2019), "Armed Conflict and Food Security in West Africa: Socioeconomic Perspective", International Journal of Social Economics, Vol. 46 No. 2, pp. 182-198. https://doi.org/10.1108/IJSE-11-2017-0538Download as .RIS
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Promoting global food security is one of the daunting challenges currently confronting world leaders. Sub-Saharan Africa appears to constitute a severe setback or drag to the worldwide initiative in promoting food security, primarily because of the regions’ inability to exploit its natural resources. For instance, it is estimated that Sub-Sahara Africa has a total of 466m hectares of uncultivated land with high agro-ecological potential in areas with the population density of fewer than 25 persons/km2 (Fischer and Shah, 2010). The uncultivated land is estimated to be equivalent to one-third of global cropland that is 1.5bn hectares (Deininger et al., 2011). In addition to being unable to harness their deposits of natural endowments optimally, Sub-Saharan Africa countries are confronted with historically persistent developmental challenges like dysfunctional and fragile political institutions, weak macroeconomic environment and undiversified economy.
Consequently, the increasing wave of armed conflicts in Africa seemingly threatens the little progress made toward promoting global food security. In West Africa for instance, Sierra Leone and Senegal made significant progress between 1997 and 2012, regarding reducing the incidences of conflicts and fatalities (Armed Conflict Local and Event Data Project, 2016). However, countries like Nigeria, Niger and Mali, that were politically stable between 1997 and 2009 have degenerated to the most conflict-prone African nations by 2015 and 2016 (Armed Conflict Local and Event Data Project, 2017). Institute for Economics and Peace (2016) Global Terrorism Index ranked Nigeria, Niger and Mali 3rd, 16th and 25th, respectively out of the 119 selected countries globally. By implication, the sub-region has recorded the highest cases of terrorism in the world. Nigeria and Niger are also ranked third and ninth of top ten countries with the highest number of deaths by terrorism. The nature and structure of these conflicts appear slightly different regarding the magnitude and intensity.
Institute for Economics and Peace (2016) indicated that “93% of all terrorist attacks between 1999 and 2014 occurred in countries with high levels of state-sponsored terror.” This thinking continues to influence some scholars to rely on four major competing theories of frustration–aggression, resource curse, relative deprivation and state failure, in explaining the trajectory in armed conflicts, political violence, militancy and terrorism in less developed countries (Maiangwa et al., 2012). Some other scholars have extended the debate by broadly classifying the causes of armed conflicts into natural and human-made factors. The natural factors include but not restricted to climate change, population size, competition and diversity (Dowd, 2015), while the human-made factors include religious extremism, security deficiency, sense of alienation, endemic elite corruption, inadequate and deceptive reporting system, military brutality, adverse economic conditions, decrepit systems and underdeveloped infrastructure (Estrada et al., 2015; Synder, 2005).
These theories argue that eliminating the natural and human-made factors is the best strategy for reducing armed conflicts. The natural factor theorists hold that climate change and property rights are increasingly linked to the risk of armed conflicts. As such, the only strategy for reducing armed conflict is eliminating human activities that promote the depletion of the ozone layer (Barnett, 2003; Barnett and Adger, 2007; Gleditsch, 2012; Hendrix and Salehyan, 2012; Raleigh and Kniveton, 2012). This view was instrumental to the strong global collaborative effort toward climate change. The human-made factor theorist emphasized the need for de-escalation of militarism and de-radicalization of extremism while arguing that the crucial elements advocacy for good governance, social justice, equality and respect for human rights and the rule of law were essential (Synder, 2005).
There is, therefore, a consensus in the empirical literature that climate change, social injustices, property right, food insecurity, religious extremism and bad governance are the predictors of armed conflict. Pinstrup-Andersen and Shimokawa (2008) explicitly argued that “poverty, hunger and food insecurity, unequal distribution of income, land, and other material goods, generate anger, hopelessness, a sense of unfairness and lack of social justice. These factors, in turn, provides a fertile ground for grievance and conflict exploited by individuals and groups with the desire to cause conflict – be it is an armed rebellion, civil war, revolution, national or international terrorism” (p. 513).
While academic positions on the role of poverty in promoting armed conflicts have been historically laid out, the practical validity of theories has not been reconciled with realities in West Africa. The trend and pattern of armed conflicts in West Africa could primarily exacerbate food insecurity, poverty hunger, hopelessness and the greenhouse effect. For instance, Boko Haram insurgents in Nigeria occupied certain territories for more than three years and displaced the rural population from their sources of livelihood. This pattern of armed conflicts reasonably disrupts all stages of human activities like production, procurement, preparation, allocation, consumption and biological utilization of food. Despite, the increasing trend of this pattern of armed conflict in West Africa, little research efforts have been made in clarifying our understanding of the impact of conflict on food security in the sub-region. In the light of the above aforementioned, this paper systematically explores the effect of armed conflict on food security in West Africa. The rest of the work is divided into Section 2 which present the stylized facts on armed conflicts and food security in West Africa; Section 3 presents the review of related literature; Section 4 discusses the methodology; while Sections 5 and 6 present the discussion of the results and the conclusion of the paper, respectively.
2. Stylized facts on armed conflicts and food security in West Africa
2.1 Armed conflicts in West Africa
Armed conflict is a significant problem confronting the global community and takes different dimension in West Africa. In Nigeria, it takes the form of Boko Haram insurgency, Niger Delta militancy, communal clashes, secessionist agitation, inter-religious conflicts and Fulani herdsmen conflict. Boko Haram, which is the second deadliest terrorist group in 2015 (see Institute for Economics and Peace, 2016) is an extremist religious group with intense concentration in Northeastern Nigeria. The group activities date back to 2002 when their activities focused on attacking government establishments such as the attack of the Nigerian Police Force Headquarters in Borno State, killings in Geidam and Kanamma in Yobe State and the stealing of ammunition for future operations (Maiangwa et al., 2012).
The group was founded to resist anything western – politics, lifestyle, dressing and education, because of the overarching belief that such practices corrupt the Islamic faith. The group’s ethos, therefore, is to purge the Nigerian society of corruption and moral decadence and establish a pure Islamic society that is devoid of western influence. Those that do not fit into this ideology are regarded as infidels and wrongdoers that must be eliminated. By 2010, the group had been encouraged and had resorted to the use of the deadly improvised bomb, suicide bombers, military arm-bush and open confrontation with law enforcement agencies like the military, government officials, public institutions, not sparing places of worship and unsuspecting innocent civilians. Since inception, the group activities have resulted in the loss over 5,478 lives as at end 2015 (Institute for Economics and Peace, 2016).
Militancy in the Niger Delta region of Nigeria is the wagging of war against the government over the continued exploitation of natural resources (crude oil) without a commensurate development of the region. The Niger Delta People Volunteer Force (NDPVF) started in 1998 but gained momentum in 2003. The objective of NDPVF was to obtain a greater share or probably the exclusive right to revenue from crude oil exploration from the region. In its first public statement in January 2006, NDPVF sought the release of the jailed NDPVF leaders – Dokubo-Asari and late Diepreye Alamieyeseigha; payment of USD1.5bn as compensation for environmental degradation by oil-producing companies, and a greater share of oil revenue (Nwogwugwu et al., 2012). NDPVF activities involve the bombing of pipelines, disruption of oil exploration, kidnaping of foreign employees of oil companies and fierce gun battle with the military. These activities of NDPVF increase fatalities, environmental degradation through oil spillage, adverse climate change and destruction of agricultural life.
The activities of herdsmen represent another major conflict source in West Africa. The conflict is as old as the history of grazing in West Africa. Episodes of herdsmen attack or conflict heightened in the last decade, with the extremely high rate of fatalities, because of the nature of the conflicts. Their activities take the form of extra-judicial killings, invasion of communities in the midnight, ensuring that victims sustain permanent disability, displacement of victims from the source of livelihood, destruction of cultivated farmlands, as well as burning down of houses. The conflicts do not only disrupt agricultural activities but also create fear and panic among the affected communities, thereby creating apathy for rural agrarian activities. The herders’ militia has killed about 630 people as at 2015, a decrease of 50 percent from 2014 figure (Institute for Economics and Peace, 2016).
Ghana regularly witnesses armed conflicts that involve different protagonists. The Northern region of Ghana has recorded the highest number of conflict in the country (UNDP, 2012). The conflicts are majorly ethnic such as the Bimbilla ethnic conflict, the Buipe, Yendi and Kpandai chieftaincy conflicts. The cause of the conflict is historically traced to the colonial policy of putting acephalous societies under the centralized states (UNDP, 2012). The conflict is similar to the Nigerian civil war and other secessionist movements across West Africa. Upper East Ghana crisis is concentrated in the Bolgatanga and Bawku areas, which is attributed to chieftaincy tussle and resource control (Assefa, 2001).
In summary, the predictors of armed conflicts in West Africa are religion – as the case of Boko Haram -, resource control – as the case of Niger Delta Militancy-, colonial policy of putting acephalous societies under the centralized states – as in the case of Nigeria and Ghana, political, among others. Despite efforts by national governments, international agencies and multinational organizations to address these conflicts, these efforts could best be described as interim or short-term measures of reducing the number of conflicts, rather than proffering a lasting or sustainable solution to the conflicts. Table AI presents a snapshot of historical armed conflicts in West Africa.
2.2 Food security in West Africa
Food security has been defined from various perspectives. World Bank (2009, p. 12) defined household food security “as year-round access to an adequate supply of nutritious and safe food to meet the nutritional needs of all household members.” FAO (2006) define food security as “people having at all times, physical, social and economic access to sufficient, safe and nutritious food which meets their dietary needs and food preferences for an active and healthy life.” These definitions are broadly classified into food availability, food access, food utilization and food stability. Candel (2018) identified the causes of food insecurity to include “changing diets, yield gaps, effects of climate change, poor governance, social inequality, the functioning of the global trade system, biofuels production, and financial speculation.” Prosekov and Ivanova (2018) also attribute the predictors of increasing food insecurity to “natural cataclysms, armed conflicts, population growth, and poverty.”
Food insecurity is a major problem confronting the entire spectrum of the globe. FAO (2017a) estimate showed that 794m people or 10.8 percent of the world population were malnourished, and this trend deteriorated in 2016 as 815m people representing 11.0 percent of the world population were malnourished. As at 2017, the total number of malnourished people in developed countries is less than 5 percent and 13 percent in developing economies, but 20 percent in Africa (Prosekov and Ivanova, 2018). At the sub-regional level, Sub-Saharan African countries are seriously lagging behind regarding concerted effort aimed at tackling food insecurity at the global level (FAO, 2017b). South Africa appeared to be one of the best performing African nation with 26.0 percent of the population malnourished, 28.3 percent at the risk of hunger and 45.6 percent food secure (see Tibesigwa and Visser, 2016).
West African countries appear worse-off in Sub-Saharan Africa. For instance, the prevalence of malnutrition among children ranges from 55 percent in Niger and 29 percent in Senegal (Haggblade et al., 2017). Sierra Leone is one of the worst performing countries in the world using Global Food Security Index as food insecurity in the country is increasing at 2.6 percent (see Prosekov and Ivanova, 2018). Future projection tends to suggest that food insecurity would also worsen in West Africa as result of climate change and increasing armed conflicts. The frequency of armed conflicts globally, which decreased to an all-time low in 2005 witnessed dramatic up-surge in 2010 and is currently assuming alarming rate. The conflicts are concentrated in four regions which include Eastern Europe, Central America, East and North Africa and Sub-Saharan Africa (FAO, 2017a). According to FAO (2017a), “many of the most protracted conflicts currently flow across borders and are regions, including in the Horn of Africa, the Great Lakes region of Africa, between Afghanistan, India and Pakistan and from Cameroon, Chad and northern Nigeria across the Sahel. This validates the report of Armed Conflict Local and Event Data Project (2017) and Institute for Economics and Peace (2016) Global Terrorism Index that West Africa represents a sub-region with increasing conflict intensity. The increasing incidence of food insecurity and armed conflicts provides substantial justification for filling this critical knowledge gap.
3. Review of related literature
Conflicts are not always violent. However, in West Africa, most conflicts are violent, which involve the use of arms and ultimately results in fatalities (Afisi, 2009; Afolabi, 2009). Economic Community of West African States (ECOWAS) has institutionalized ECOMOG as a conflict resolution mechanism within the sub-region. This initiative is expected to reduce conflict in the sub-region efficiently. However, the strong focus of ECOMOG on political conflicts, involving member states, appears to limit its scope. As such, the ECOMOG initiative is not designed to tackle the recent and more worrisome dimensions of armed conflicts in the sub-region. The gorilla nature of recent uprising and insurgencies that have affected Mali, Niger, Nigeria and Mauritania, has emphasized the need to rethink conflict resolution strategy in the region. Olonisakin (2011) observed that there is also Casamance conflict in Senegal, the Niger Delta/Boko Haram conflict in Nigeria and Dagbon chieftaincy crisis in Ghana.
The consequences of these crises are the loss of lives, destruction of properties, increase in some displaced persons/refugee crisis, widening poverty cycle, disease prevalence, drug-related criminality and proliferation of small arms. Other consequences include the illegal appropriation and use of natural resources/banditry, food shortage through the interrupted production of food and even destruction of physical and natural infrastructure (Afolabi, 2009). Armed conflicts resolution in West Africa is one of the daunting problems facing the sub-region. The difficulty is primarily attributed to the multifaceted nature of the conflicts and their respective causes. Jaye et al. (2011) argued that conflicts have diverted the focus of sub-regional economic blocs such as ECOWAS from economic integration to conflict resolutions. For instance, ECOWAS held a conference from April 26 to 29, which was attended by all ministers of Interior and Agriculture of the member states and non-member states of Central Africa Republic and a host of others affected by the dreaded activities of herdsmen. The conference aims to review the May 1979 Free Movement Treaty and develop a framework for sharing regional data on the movement of people and goods, to end the constant herdsmen/farmers conflicts in the sub-region. Channeling funds for such conferences naturally retards the growth of the sub-region by eroding the benefits that would have accrued from well-focused and targeted economic and sub-regional integration.
Importantly, armed conflicts in Northern Mali, Northeastern Nigeria and the Central African Republic have resulted in the displacement of rural populations (FAO, 2015). The displaced population currently settles in Burkina Faso, Cameroon, Mauritania, Niger and Chad, or neighboring states within the country. The influx of displaced persons is putting pressure on the existing resources and precipitate conflicts and humanitarian crises. In pointing out the crippling effect of violent conflicts, FAO (2015) reports highlights dangerous effects of armed conflicts on food security in the absence of any concerted effort to tackle the problem. The report mostly highlights the adverse impact of armed conflicts on the displacement of people and the consequent humanitarian crisis.
The relationship between armed conflict and food insecurity mostly focus on the role of poverty in promoting conflicts. This stream of literature argued that reducing the incidence of poverty and income inequality would automatically mitigate global conflicts. According to Borlaug (2004), cited in Pinstrup-Andersen and Shimokawa (2008), “we cannot build a world of peace on an empty stomach.” This citation suggests that armed conflicts predictors are hunger, poverty, deprivation and deprivation. The above position radically influenced the global collaboration and advocacy for aids and grants to less developed countries, with prevailing high poverty rate and income inequality.
On the contrary, the “greed and grievance hypothesis” has been used to diffuse the traditional theory that food insecurity is the predictor of armed conflict. The greed and grievance theory argue that greed and grievances – from bad governance, injustice, political right, among others, could incite violence and conflict, in the presence of abundance. Collier and Hoeffler (2004) argue that conflicts are mostly consistent with the “economic interpretation of rebellion as greed-motivated.” While holding out that rebels are not necessarily criminals, Collier and Hoeffler (2004) found out that the grievances that motivate rebels are most often, substantially disconnected from such social concerns such as inequality, food insecurity and political rights, among others. Such grievances motivated conflict could, therefore, threaten food security. Hendrix and Brinkman (2013) in addressing the issue of causation between food insecurity and conflict, using the SAHEL region as a case study, found out that increase in both the number of active conflicts and its intensity has closely been followed by a persistent rise in international food prices notably between 2010 and early 2011. The findings of these studies have once again raised the question of whether food insecurity causes violent conflict or is it a case of reverse causation. The work provokes an argument along the line of deemphasizing unidirectional explanations of the food security/conflict relationship.
Jeanty and Hitzhusen (2006) applying instrumental variable (IV) panel data techniques estimated the effects of civil wars and conflicts on food security in developing countries. From a statistical standpoint, the study brought to fore the danger of using conventional panel data estimators when endogeneity is of conventional type. It was found that civil wars and conflicts are detrimental to food security and are even more damaging for developing countries that can barely meet the dietary requirements of its citizenry. Similarly, Sambe et al. (2013) x-rayed the impact of communal violence on food security in Africa. The study which is underpinned by the Marxist theory which emphasizes on group interest and competition for resources as the major driver of violent conflict in climes such as West Africa held that armed conflicts affect food security and makes access to food almost impossible. This is caused by the destruction of arable land, physical infrastructure, forest and livestock reserves and many other critical food production infrastructures. Besides, the study brought out the impacts of conflict to include displacement of labor and the unsavory use of food as a weapon of war.
Chen et al. (2015a, b) uncovered linkages between commodity prices and conflict focusing on the conflict-ravaged Sudanese economy. Though the causal direction of the relationship remains ambiguous, using data sets covering periods from January 2001 to December 2012, they adopted a structural breakpoint test in the multivariate time series model of prices to study the impact of conflicts on food prices. The study chose the prices of three staple food items, namely, sorghum, millet and wheat, and the number of conflict event as the proxy for conflict. The original estimation techniques were structure vector autoregression, and Linear Non-Gaussian Acyclic Model and the finding holds among other things that the prices of wheat in Sudan increased as conflict events rose.
In West Africa, armed conflicts take the form of occupying territories, displacement of rural people – who are predominantly agrarian – from their source of livelihood, pipeline vandalization that results in oil spillage, destruction of natural habitation and disruption of production activities. This form of conflicts could change the direction of causation between conflicts and food security. Importantly, it could be the case of armed conflicts causing food insecurity. Using data from West Africa to reconcile this important theory contributes extensively to theoretical and empirical literature, as well as, the formulation and implementation of policies that responds sensitively to conflict resolution.
To test the effect of armed conflict on food security, we used annualized panel data set that spans from 2005 to 2015. We chose this data range because of the timing of the research. We are also conscious of the problem of data unavailability and the need to minimize the number of missing observations in our baseline estimation model. The selected West African countries are Nigeria, Ghana, Sierra Leone, The Gambia, Guinea, Guinea Bissau, Senegal, Benin, Togo, Cote d’Ivoire, Liberia, Mali, Burkina Faso and Niger. We dropped Cabo Verde from the observation because of non-availability of data.
Food security constitutes the dependent variable. FAO (2006) defined food security as “people having at all times, physical, social and economic access to sufficient, safe and nutritious food which meets their dietary needs and food preferences for an active and healthy life” and uses five methods in assessing food insecurity. The five methods are “calories available per capita at the national level; household income and expenditure surveys; individual’s dietary intake; anthropometry; and experience-based food insecurity measurement scales.” The first four methods are indirect and place the analytical spotlight on derivative measures or nutrition-based measures of food security. The last method – experience-based food insecurity scale – is a direct or fundamental measure of food security that complements other methods.
We adopt the experience-based food insecurity scale based on the objective of the paper since we suspect that armed conflict could fundamentally disrupt production processes given the nature and trend of the conflicts in West Africa. This is a standard departure from the nutrition-based measures with the analytical spotlight on production-based measures (Chen et al., 2015a, b; FAO, 2010). Most armed conflicts are rural, and conflict intensity would have adverse effect crop, forestry and livestock production in the sub-region. We adopted the natural logarithm of the weighted average of crop, forestry and livestock production as a proxy for food security. The intuitive appeal of the selected proxy is substantially influenced by the fact that armed conflicts in West Africa, because of their rural nature, will adversely affect the production of the crop, forestry and livestock. The data were collated from FAO database, and we adopted FAO definition of crop, forestry and livestock production.
The major explanatory variable is conflict intensity. Conflict intensity is defined in line with ACLED as “political violence on civil and communal conflicts, violence against civilians, militia interactions, rioting and protesting” (Ezeoha and Ugwu, 2015). Prosekov and Ivanova (2018) demonstrated that regions with reduced armed conflicts experience more food supply than regions with active conflict. Similarly, FAO (2017a, b) recent statistics showed that of the 815m chronically food insecure and malnourished people in the world, vast majority representing approximately 489m or 60 percent live in countries, affected by conflict. Such anecdotal evidence re-enforces the imperativeness of empirically evaluating the effect of conflict intensity on food security. We estimated conflict intensity using the natural logarithm of the total number of fatalities in each year (Ezeoha and Ugwu, 2015). To make our findings comparable with previous empirics, some theoretically important control variables were introduced to the baseline model. The variables are the natural logarithm of arable land as a percentage of the total land area; natural logarithm of improved water sources; natural logarithm of a percentage of rural population with access; and the natural logarithm of the amount invested for agricultural research and development.
Table I depicts the definitions of the baseline variables, the data sources and descriptive results. The choice of the moderating variables stems mainly from the interactive influence they arguably exert on food production particularly and by extension food security. The measures of aggregative tendencies such as mean and median are presented alongside measures of spread and variation like standard deviation, minimum and maximum. Conflict intensity with a standard deviation of 377.5 and a mean of 107.1 lying between a minimum and maximum of 2 and 3,905 respectively, tends to be the variable with the highest variation. This apparently shows the volatile and spatial nature of armed conflict in West Africa. Conversely, food security’s standard deviation of 126.1 and a mean of 706.9 lying between a minimum of 666.7 and a maximum of 1,972 follows closely. This arguably is not unconnected with the slow growth and spatial pattern of food production and security in West Africa.
4.2 Empirical technique
We investigate the dynamic linkage between armed conflict and food security for West African countries in the period 2005–2015 using the generalized method of moments (GMM) dynamic model with a balanced panel data (Arellano and Bond, 1991; Blundell and Bond, 1998). The use of panel data enables us to investigate the dynamic relations between armed conflict and food security, as well as controlling for the unobserved heterogeneity of the 14 selected ECOWAS countries. In examining the linkage between armed conflict and food security, reverse causality becomes an issue since past empirical literature has also established that causality runs from food security to armed conflict, and not merely vice versa. Thus, resolving the problems of causality and dynamics become crucial to the analyses of our hypothesized link and justifies our decision to use the GMM. First, we state the general framework for a static panel study as:
As states earlier, some of the variables are endogenous in nature (see Ezeoha, 2013; Buch and Kuckulenz, 2009; Adams, 2009). To address the probable endogeneity problems that might be present in Equation (2), we apply an IV regression model, based on the GMM) technique. We validate the instruments by adopting Roodman (2009) through the imposition of lags to reduce the proliferation of instruments. The lag of the dependent variable is used to indicate the dynamics in the model as shown in the following equation:
5. Discussion of results
Table II presents the static model approach and reports the baseline results of Equation (1) using food security as the dependent variable. Models 1, 2, 3 and 4 show the pooled OLS, FE model results, LSDV and RE models, respectively. The predictive value of the exogenous variable of interest which is conflict intensity as well as the moderators was displayed in Table II. The results of the static panel analyses revealed the mixed results and did not form the basis for our estimation because of the limitations of generalized least square (GLS). Specifically, the GLS estimator involves quasi-demeaning the data, which causes the dependable variable to be correlated with the quasi-demeaned residuals, making the GLS estimator biased and inconsistent. Aside from the above limitation of GLS estimator, we are also interested in the dynamic behavior of the variables. These factors influenced our decision to adopt the dynamic GMM since the dynamic model has the tendency to overcome the deficiencies of the static model (Arellano and Bond, 1991; Blundell and Bond, 1998).
Table III also presents the results of the dynamic panel difference GMM models (Arellano and Bond, 1991). Models 1 and 2 represent the one-step Arellano–Bond GMM estimator, while models 2 and 3 present the two-step Arellano-Bond GMM estimator. Our decision to migrate to two-step Arellano-Bond GMM estimator is based on the fact that it yields a more asymptotically efficient estimate compared to one-step. The results that collapse the instrument matrix followed Roodman (2009) which is considered more efficient since it strives to limit spuriousness of the results that might be associated with the proliferation of instruments. As shown in Table III, all the models predict that armed conflict has a significant negative effect on food security, indicating that conflict intensity leads to decline in food production.
However, there are diagnostic issues with the result. The Sargan test in the result of the collapsed instrument matrix suggests the presence of the likelihood of over-identification and misspecification problems (DGMM1-CL- (a) 0.01 and DGMM2-CL-(a) 0.0193) (see Roodman, 2006). This indicates a possible correlation of the residuals and the IVs. Though the Hansen tests and the AR (1) and AR (2) show that there is a proper correction of serial correlation, there are inherent limitations of the difference GMM for which cause we settled for the system-GMM in estimating the relationship between conflict intensity and food security. One major problem with the difference-GMM is that lagged levels are poor instruments for the first difference if variables are close to a random walk (Bond 2002; Roodman, 2009; Sarafidis et al., 2009).
The weaknesses associated with difference-GMM influenced our decision to migrate to the system-GMM since it produces a more consistent estimator in the face of persistence in series. This it does, by addressing large sample bias in the face of additional moment conditions (Blundell and Bond, 1998, 2000, Roodman, 2009). In the light of the preceding, the system-GMM forms our basis for measuring the relationship between armed conflict and food security over and above the static models and the Diff-GMM. We also adopted the one-step and two-step estimators based on reasons previously discussed.
The results of the system-GMM in Table IV reveal that armed conflict has a significant negative effect on food security. Even the lagged values of armed conflict have a significant negative effect on food security, suggesting that the present and past conflict intensities could lead to food insecurity in the region. To circumvent general problems associated with system-GMM, which the proliferation of instruments (presence of more instruments than the regressors) or the specification is over-identified, that renders the estimates invalid, we impose and implement the Roodman (2009) prescriptions. Based on that, we adopt the results of the system-GMM Models 2 and 3, which is two-step and follows Roodman (2009) by limiting the spuriousness of the results that might be associated with the proliferation of instruments.
Specifically, the number of instruments is 11 for both models and the study covered 14 countries which show the absence of proliferation of instruments that might bias the results. The results also suggest the absence of misspecification and serial correlation problems as shown by the Sagan and Hansen tests, respectively. The results show that lagged armed conflict or conflict intensity, research expenses, arable land and water access have significant impacts on food security in West Africa. While conflict intensity or armed conflict has a significant negative effect on food security; research expenses, arable land and water access are found to be positive determinants of food security in West Africa.
Extant literature has used theories of frustration–aggression, resource curse, relative deprivation, state failure and climate change to explain the causes of armed conflicts, especially in less developed countries. The studies attributed the increasing wave of conflict to poverty, hunger and food insecurity, unequal distribution of income, struggle for resources and other material goods, anger, hopelessness, sense of unfairness and lack of social justice. Specifically, these studies suggest that food insecurity promotes armed conflicts. While we are not contesting the results of these previous studies that found food insecurity as a major determinant of armed conflict, it is imperative to empirically validate the anecdotal evidence provided by FAO (2017a) that persistent and increasing armed conflict especially, in Africa could lead to food insecurity. Specifically, it is crucial to establish whether the nature of armed conflict in Africa could hurt food production. For instance, it is extremely important to establish whether the nature of armed conflicts in West Africa, especially, herdsmen and Boko Haram conflicts that lead the destruction of farmlands, occupation of territory, results in high rate of fatalities, displacement of rural population from their source of livelihood, could adversely affect agricultural activities (production), as well as exert pressure on the existing food bank since the dislocated rural farmers end up in internally displaced persons camps .
The empirical results reveal that armed conflict has a significant negative effect on food security in West Africa. The study, therefore, recommends that global initiative to combat food insecurity must first, identify the causes of armed conflicts, especially in Africa, and design genuine strategies for de-escalating the conflicts. The conflict resolution framework must be extremely sensitive to the causes of conflict in Africa. For instance, the framework must be sensitive to the predictors of armed conflicts in West Africa such as religion, resource control, colonial policy of putting acephalous societies under the centralized states, bad governance, greed and grievance. This will guide the proffering of long-term solutions rather than focusing energy on reducing the conflicts. The framework could adopt localized ex ante institutional diagnostics that would help in understanding how the local institutions work. This will help in the designing of new practices or re-arrangement of existing institutions to eliminate the sources of armed conflicts and promote sustainable food security in Africa.
Summary statistics on food security and the independent variables used in the estimation
|Description||Mathematical denotation||Obs||Mean||SD||Min.||Max.||Data source|
|Conflict intensity||Number of fatalities arising from conflicts||Natural logarithm of conflict intensity (lnconflict_Intenesity)||266||10.05||377.482||2||3,905||ACLED Project|
|Food security||(1) Crop production for 173 products, covering crops primary, fiber crops primary, cereals, coarse grain, citrus fruit, fruit, jute and jute-like fibers, oilcakes equivalent, oil crops primary, pulses, roots and tubers, treenuts and vegetables and melons; (2) Forestry Production is the number of production in roundwood, primary wood and paper; and (3) Livestock Primary Production covered the production of meat, egg, milk, wool and honey||Natural Logarithm of food security (lnfood_security||266||706.85||126.060||666.67||1,972||FAO|
|Research expenses||Total amount of money spent of agricultural research||Natural Logarithm of Research Expenses (lnresearch_expenses)||266||0.5448||0.3336||0.002||1.565||FAO|
|Water access||Improved water source, rural (% of rural population with access)||Natural Logarithm of Water Access (lnwater_access)||266||55.783||13.486||28||84.4||World Bank Development Indicator|
|Arable land||Arable land as a percentage of total land area in the country||Natural Logarithm of arable land (lnarable-land)||18.612||12.314||3.662||52.7977||World Bank Development Indicator|
Effects of armed conflict on food security (static panel models)
|Model 1||Model 2||Model 2||Model 4|
|lnconflict_intensity||−0.319*** (0.0422)||0.0186*** (0.00536)||−0.0166*** (0.00437)||0.0168*** (0.00442)|
|lnreseach_expenses||0.238** (0.0921)||0.0322*** (0.00785)||0.0331*** (0.00755)||0.0329*** (0.00763)|
|lnarable_land||0.0767 (0.0987)||0.362*** (0.0386)||0.272*** (0.0386)||0.273*** (0.0388)|
|lnwater_access||0.657** (0.265)||0.926*** (0.0555)||0.926*** (0.0555)||0.923*** (0.0559)|
|Constant||7.406 (0.482)||4.678 (0.0701)||4.646 (0.0730)||4.673 (0.148)|
|Number of id||14||14|
Notes: Standard errors are shown in parentheses. *p<0.1; **p<0.05; ***p<0.01
Effects of armed conflict on food security (dynamic panel models)
|Model 1||Model 2||Model 3||Model 4|
|lnconflict_conflict||−0.0152*** (0.00365)||−0.0132*** (0.00459)||−0.0131*** (0.00365)||−0.0110* (0.00575)|
|lnreseach_expenses||0.0200** (0.00814)||−0.00303 (0.00892)||0.0205 (0.0205)||0.00888 (0.0129)|
|lnarable_land||0.269*** (0.0925)||0.391*** (0.0959)||0.295 (0.246)||0.402*** (0.132)|
|lnwater_access||0.943*** (0.150)||0.787*** (0.152)||0.930*** (0.290)||0.841*** (0.237)|
|Number of id||14||14||14||14|
|No. of Instruments||161||10||147||9|
Notes: Robust standard errors are shown in parentheses. DGMM1 & DGMM2 denote one-step and two-step diff-GMM respectively. Regressions with suffix “CL” follow Roodman (2009) and collapse the instrument matrix. a denotes lag (1 5). *p<0.1; **p<0.05; ***p<0.01
Dynamic panel data analyses-system-GMM
|Model 1||Model 2||Model 3||Model 4||Model 5|
|L.lnarmed_conflict||−0.820*** (0.00676)||−0.686*** (0.0201)||−0.686*** (0.0200)||−0.593*** (0.118)||−0.063*** (0.0628)|
|lnarmed_conflict||−0.302** (0.124)||−0.249** (0.112)||−0.125* (0.155)||−0.136* (0.0726)||−0.126*** (0.159)|
|lnreseach_expenses||0.243** (0.200)||0.228** (0.184)||0.0566** (0.283)||0.120** (0.193)||0.0691** (0.224)|
|lnarable_land||0.0742*** (0.355)||0.0675*** (0.375)||0.117*** (0.468)||0.856*** (0.772)||0.349*** (2.107)|
|lnwater_access||0.680* (1.260)||0.692** (1.278)||0.572** (1.525)||0.171** (0.769)||0.455** (1.795)|
|Constant||0.073 (0.361)||0.062 (0.384)||0.002 (0.740)||0.068 (0.433)||0.030 (0.214)|
|Number of id||14||14||14||14||14|
|No. of Instruments||165||11||11||26||18|
Notes: Robust standard errors are shown in parentheses. SGMM1 and SGMM2 denote One-Step & Two-Step GMM respectively. Regressions with suffix “CL” follow Roodman (2009) and collapse the instrument matrix. a, b and c denote lag(1 5), Lag(1-4) and lag(2 4), respectively. *p<0.1; **p<0.05; ***p<0.01
Nature of conflict in West Africa
|S. No.||Title of conflict||Country||Date started||Date ended||Source|
|1||Revolutionary United War||Sierra Leone||1991||2002||Richards (2003)|
|2||National Patriotic Front War||Liberia||1989||2003||Human Rights Watch (2005)|
|3||Movement for the Emancipation of the Niger Delta and correlated Agitations||Nigeria||Pre-independence era||On-going||E-international relations publishing|
|4||Boko Haram and related insurgency||Nigeria and other Chad Basin Countries||2002||On-going||Agyapong (2005)|
|5||Nigerian Civil War and Continuing Agitation for the sovereign state of Biafra||Nigeria||1967||Ended 1970, agitations on-going via non-violent means with frequent state clampdown||E-international relations publishing|
|7||Coup d’état and ethnic related crises||Mali||2007||2012||BBC News Africa (2012)|
|8||Weapon trafficking triggered Conflict||Guinea Bissau||June 1998||May 1999||Voz di Paz and Interpeace (2010)|
|9||Post-Houphouet-Boigny Political Uprising||Ivory Coast||September 2||2007||Ogwang (2011)|
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The authors of this paper have not made their research data set openly available. Any enquiries regarding the data set can be directed to the corresponding author.