# Does youth resentment matter in understanding the surge of extremist violence in Burkina Faso?

31 October 2023

Tebkieta Alexandra. Tapsoba, Researcher, Institut Supérieur des Sciences de la Population, Université Joseph Ki-Zerbo, 03 BP 7118 Ouagadougou, Burkina Faso. ORCID: https://orcid.org/0000-0001-9238-853X

Email address: teb_kieta@hotmail.com; atapsoba@issp.bf

Jean-Louis Combes, Professor, Laboratoire d'Economie d'Orléans, Université Clermont Auvergne, 63000 Clermont-Ferrand, France. ORCID: https://orcid.org/0000-0002-2636-3155

Email address: j-louis.combes@uca.fr

Pascale Combes Motel, Professor, Laboratoire d'Economie d'Orléans, Université Clermont Auvergne, 63000 Clermont-Ferrand, France. Corresponding author. ORCID: https://orcid.org/0000-0002-3532-2339

Email address: pascale.motel_combes@uca.fr

Phone number: +33 4 73 17 74 13

## Acknowledgements

The authors thank Dr Dabire Bonayi, Dr Onadja Yentema, Dr Wayack-Pambe Madeleine, and UNICEF Burkina Faso for making the data accessible. The authors are grateful to the 2021 Association Française de Sciences Economiques Annual Conference participants. They would like to thank the Editor-In-Chief (Francis Teal) and an anonymous referee for their valuable comments and suggestions. Usual disclaimers apply.
# Does youth resentment matter in understanding the surge of extremist violence in Burkina Faso?

## Abstract

The year 2019 marked an unprecedented step in violence in Burkina Faso. Before 2018, attacks targeted central government officials and expatriates. In 2019, the victims of sexual assaults, attacks, abductions or forced disappearances, and assassinations were mostly local civilians. The surge in these violent attacks against civilians generates population movements. As of 2023, internally displaced people represent about 10% of the total population in the country. Several observers point to the youth of the attackers. This study investigates the motives that could drive young people to resort to violence in the country. It aims to highlight youth resentment's effect on violence against civilians in the country as of 2019. It takes advantage of one of the latest nationwide UNICEF-sponsored surveys conducted in Burkina Faso before some parts of the country became inaccessible because of attacks. Among other information, this survey collected data on youth resentment towards the ability of their kinship to fulfil their needs in 2018, namely before the shift in violence against civilians. We merge this survey into an original dataset that gathers data from the Armed Conflict Location and Event Data Project (ACLED), mining data from the MINEX project, and distances data computed using Burkina Faso's roads information. The results of an event count model show that youth resentment matters in understanding the occurrence of conflicts. Moreover, the presence of mining companies, the remoteness of infrastructures, ethnic diversity, and polarisation also significantly affect violence against civilians.

## Keywords

Conflicts, Youth resentment, Relative deprivation, Burkina Faso

## JEL Codes

D74 J13 O55
# 1 Introduction

> "Of course, there are Fulani among the jihadists ... But no more than in other ethnic groups. When armed groups offer young people in poverty and without education the chance to take up arms and get money, they are tempted. And it's not because he belongs to this or that group."<fnref n="1" />

What motives drive individuals to rebel by enrolling in an armed group? Motivations are many (see, for instance, (Humphreys & Weinstein, 2008)). Some motives, such as ideology or social pressure, arguably play a crucial role. This study, however, addresses this question from an economic standpoint that draws attention to economic grievances and perceived relative deprivation. We focus on young people who are the most likely to join armed groups (see, e.g., (Cachalia, Salifu, & Ndung'u, 2016) in the case of Africa). We assess the hypothesis according to which youth resentment regarding the ability of households to fulfil their economic needs incentivises them to join violent armed groups. Our underlying assumption is that young people face a trade-off between the benefits and costs of violence: we hypothesise that whenever households unsatisfactorily meet the needs of young people, the latter is more likely to resort to violence, other things held equal. This approach is consistent with the literature according to which violent groups may also provide "services" to their members (see, e.g. (Dixit, 2004)). We test this hypothesis in the case of Burkina Faso, which experienced increased attacks by armed groups in 2019. The year 2019 marked an unprecedented step in violence in Burkina Faso. Before 2018, attacks targeted central government officials and expatriates. In 2019, the victims of sexual assaults, attacks, abductions or forced disappearances, and assassinations were mostly local civilians.

Terrorism in Burkina Faso is a multifaceted phenomenon, arguably fed by socioeconomic conditions and the Government's poor management (Savadogo, 2019). It severely hurt civilians and fostered displacement. According to the UN Office for the Coordination of Humanitarian Affairs, as of January 2023, internally displaced persons in Burkina Faso now represent more than one million persons (about 10% of the population).<fnref n="2" /> In this study, we take advantage of the latest nationwide UNICEF-sponsored survey (2018) before some parts of the country became inaccessible because of insecurity. This survey allows investigating the resentment of Burkina Faso's youth, which constitute the bulk of

<footnote n="1">¹ This citation emanates from a tribal chief of the Sahel region (Gonin, 2020).</footnote>

<footnote n="2">² See e.g. https://reliefweb.int/report/burkina-faso/burkina-faso-apercu-des-personnes-deplacees-internes-31-janvier-2023 (in French).</footnote>
the population from which armed groups recruited just before the upsurge in attacks on civilians in 2019. This survey offers a rare opportunity to quantitatively capture the youth's feelings on the ability of their household to fulfil their needs, namely to feed, clothe, heal them in case of sickness, and offer them gifts. We econometrically assess our hypothesis while augmenting this survey with other relevant quantitative information. We specifically use data from the Armed Conflict Location and Event Data Project (ACLED), mining data from the MINEX project, and distance data computed using Burkina Faso's road information. We implement an event count model, namely a negative binomial regression. This econometric methodology evidences that youth resentment measured in 2018 positively and significantly correlates with conflicts targeting civilians observed in 2019. We focus on 2019 because this year represents a significant change in both the number and the nature of terrorist attacks. Moreover, the presence of mining companies, the remoteness of the city capital, ethnic diversity, and polarisation also significantly affect violence against civilians.

We organise the rest of the article as follows. Section 2 describes the political context in Burkina Faso and the events that preceded an increase in terrorist attacks in 2019. Section 3 proposes a theoretical framework adapted to Burkina Faso's reality to examine young people's drivers towards rebellion. Section 4 presents data and descriptive statistics. We discuss the econometric analysis in section 5. Lastly, concluding remarks are provided in section 6.

## 2 Violent attacks in Burkina Faso – the 2019 shift

According to UNDP, Burkina Faso is representative of state disintegration. Resentment has been nurtured on institutions and services being increasingly perceived as confined in urban and suburban zones (United Nations Development Programme, 2023). In the following, we document the rise of violence in Burkina Faso in the 2010s and then focus on the 2019 shift covered by our econometric analysis.

### 2.1 The rise of violence in Burkina Faso in the 2010s

The harmony reigning for hundreds of years within the Burkinabè population has long made this country famous. Burkina Faso counts more than 60 ethnic groups. One common feature they share is the “joking kinship” (“parenté à plaisanterie”) (Nyamba, 2001). This practice consists of making fun of another ethnic group, all in a joking way. Despite this social norm contributing to peace in the country, some secular conflicts still linger and are spread nationwide. Farmers' and herders' conflicts are
examples of such recurrent conflicts (see, e.g., the recent study conducted by (McGuirk & Nunn, 2020)).<fnref n="3" />

Climate conditions and the political developments since 2014 exacerbate these conflicts (Sanfo, Savadogo, Abalo, & Zampaligré, 2015). The year 2014 was historical for Burkina Faso, as an insurrection led to the departure of President Compaoré, who had been in office for 27 years. Two years after he left office, an unprecedented number of attacks are recorded almost daily throughout the country. On January 15, 2016, the country recorded its first-ever large-scale terrorist attack, targeting a hotel and a restaurant mainly frequented by expatriates, killing 30 people. This attack occurred two days after the newly elected president, Kaboré, set up his Government (Roger, 2016). This attack marked the beginning of violent episodes, which we statistically detail in Section 2.2. For some, this might be a coincidence, but not for everyone. In an interview with the Belgian press, the newly elected president stated that the social peace Burkina Faso has been enjoying for years resulted from a deal between former president Compaoré and terrorist groups (Köpp & Quenum, 2019). As he refused to honour some engagements the former president had with terrorist groups, violence increased. Several observers share this point of view and attribute links between military dignitaries and Lyad ag Ghali, a known Malian jihadist who belongs to the GSIM (Group for the Support of Islam and Muslims) (Malagardis, 2018). The GSIM claimed the attack against the French embassy and the main military base in Ouagadougou in March 2018, killing eight people (Le Monde, 2018). Alongside GSIM, several jihadist groups and Katiba operate in Burkina Faso and the three-border zone (Mali, Burkina Faso, Niger). The Islamic State is represented in the area with the Islamic State in West Africa Province (ISWAP), including the Islamic State in the Greater Sahara led by Abou Walid al-Sahraoui. These foreign jihadist groups targeted foreign people and State representation such as military and police stations. However, Burkina Faso later started to record new forms of violence targeting nationals and perpetrated by a home-grown jihad, leading to the internal displacement of people. This new state of affairs, i.e. the shift of targets and the shift of violence's perpetrators, also led to a shift of the blame. Thus, public opinion started to blame the Fulani ethnic group.

## 2.2 The 2019 shift

According to the UN, Burkina Faso recorded a number of 80 people killed by terrorist attacks in 2016. This number reached 1,800 people in 2019 (United Nations Office for the Coordination of Humanitarian Affairs, 2020). The Acled data corroborate this dramatic increase. Figure 1 and Figure 2

<footnote n="3">³ The Burkinabè Ministry of Justice records other land conflicts such as those between landowners and the government, royal succession conflicts, and other miscellaneous conflicts such as interreligious and inter ethnics conflicts (Ministère de la Justice, 2015).</footnote>
graph the dynamics of violent attacks against civilians from the Acled data (Raleigh, Linke, Hegre, & Karlsen, 2010). The rise in violence started in 2016 (Figure 1) under newly elected president Kaboré (see Section 2.1), while protests and riots increased from 2011 after a mutiny in the armed forces (Figure 2). While the number of protests and riots and their related fatalities does not exhibit any specific change, 2019 marks an abrupt increase in the number of violent attacks against civilians and the associated fatalities.

Burkinabè civilians actually became a target for armed groups. The International Center for Counter-terrorism argues that by 2019, the country experienced the most significant rise in terrorism-related deaths, with a percentage of 590% (Demuyinck & Coleman, 2022). In 2019, these fatalities were in the Liptako-Gourma region, along the border of Mali and Niger. One crucial fact is that the Fulani ethnic group mainly populates this region. It led to a new shortcut, blaming the Fulani for increasing attacks against civilians. Several radicalisation biographies showed that most young people joining jihadist groups in Burkina Faso, Mali, and Niger are indeed Fulani (de Bruijn M., 2018). The question might be why this ethnic group is over-represented in armed groups. According to de Bruijn (2018), extremist groups exploit the intra-community tensions within the Fulani. They are rooted in the hierarchical organisation of castes or clans. Fulani are either *Dimo* or *Rimbe* (free men) or *Nyeenybe* (people of the caste). *Maccudo* and *Riimaaybe* constitute the “slaves” category (Tamari, 1991). Even though slavery no longer exists, people of *Riimaaybe* or *Maccudo* origin are still less considered than others (de León Cobo & Rodríguez González, 2020). The cleavage between the Fulani “masters” descent and the *Riimaaybe* from slave descent remains in the Sahel regions. The former cast is more affluent, most respected, and higher in society, while the latter is more impoverished and socially low.

Henceforth, armed groups present jihad as a social promotion channel by breaking down the traditional order and creating an order in which faith is above social groups and castes (Thiam, 2017). Ansaroul Islam founded by the Burkinabè preacher Malam Dicko,<fnref n="4" /> a native of the Sahel region, has been responsible for many attacks against civilians. He argued that the organisation of the Fulani in the North and the marginalisation based on castes are contrary to Islam. Dicko further denounced the chiefdom organisation of the society and the cleavage between Fulani masters' descent and the *Riimaaybe* (Le Roux, 2019). He advocated for equality between the population and the end of marabout families' enrichment at the expense of poor people.<fnref n="5" /> When Ansaroul Islam groups started their operations, they aligned with their speeches. Their exactions include the assassination of the

<footnote n="4">⁴ He has been allegedly killed in 2017, but his death has never been confirmed.</footnote>

<footnote n="5">⁵ Being an Imam is inherited in this society due to history. New Muslim scholars such as Malam thought religious authority is not only for a selective few (International Crisis Group, 2017).</footnote>
leaders of this aristocratic society, such as spiritual guides, teachers, and government workers.
Between 2016 and 2018, a report by Human Rights Watch (HRW) argues that most of the victims of
“execution-style” killings by Islamist armed groups were village chiefs and local officials in the Sahel
region (Human Rights Watch, 2018). The organisation also attacks state representation. The first one
was the attack on the police station in Nassoumbou that killed twelve soldiers in December 2016
(International Crisis Group, 2017). Like Dicko, speeches echoed perfectly to unemployed and socially
rejected young men who joined the cause. Hence, according to HRW, some Fulani community leaders
were since 2015 concerned about the Islamists' exploitation of young people's frustration with
poverty, government corruption, security forces' abusive behaviour and the Fulani clan leadership
(Human Rights Watch, 2018). Another factor contributing to the reinforcement of Fulani young men
into radicalisation is the Government's response to terrorism. It sometimes leads to abuses, as stated
in the previous paragraph. Also, ethnic militia sometimes seek revenge for the attacks they face by
doing justice themselves. The well-known Yirgou drama, where 46 Fulani people lost their lives
(according to the Government and 216 according to NGOs), is yet to be adequately investigated (Le
Faso.net, 2020). This lack of justice and desire for revenge make it easier for armed groups to recruit
young Fulani people (de León Cobo & Rodríguez González, 2020).

Insert Figure 1 and Figure 2 (to be found in Section 8)

Several causes may explain the surge in terrorist attacks. However, young men's frustrations regarding their social status and fulfilling their basic needs deserve careful attention.

## 3 Why do youth rebel?

Black (1972) reviewed Gurr's book "Why men rebel."<fnref n="6" /> He argues that the process that leads men to violence goes through three stages. The rebellion begins with frustration and discontent. Then, these feelings undergo a political transformation that can, in turn, lead to violence. Discontentment arises from the gap between what an individual thinks she deserves and what she believes she will get, given her living standard. This process gives perceived relative deprivation (Gurr, 2015, p. Chapter 2).<fnref n="7" /> (Yitzhaki, 1982) defines deprivation as a loss of utility due to a lack of commodity. This deprivation is

<footnote n="6">⁶ The book was first published in the 60s and addressed the violence occurring in postcolonial states in Africa and Asia.</footnote>

<footnote n="7">⁷ There is a vast literature on the concept of relative deprivation that has been discussed within numerous disciplines. One seminal contribution dates back to (Merton, 1968) who analysed under which circumstances individuals or groups engage in deviant behaviors conducive to anomie.</footnote>
relative to a reference group. There is a vast literature on relative deprivation (Smith & Pettigrew, 2014) and, in particular, its link with the revolts (Power, Madsen, & Morton, 2020). In particular, some work has sought to show the role of relative deprivation as a factor fueling socio-political instability (concerning the Arab Spring, see: (Korotayev & Shishkina, 2020). Siroky et al. (2020) assess how relative privation impacts collective violence. Kunst and Obaidi (2020) borrow the argument to explain extremism violence. The politicisation and violence that stem from relative deprivation appear when people view the existing political regime as unworthy of respect and legitimacy. Hence, they may see violence as an appropriate response to their problems. De Bruijn and Both argue that young people in Mali and Chad see the State authority as illegitimate (de Bruijn & Both, 2017). They seek a new legitimacy worthy of their trust and respect, which they think they will find in ethnic militias or armed groups.

It is striking that most arrested fighters are often young in the three-border zone. The question may be, why? Childhood and adolescence are two sensible stages individuals go through. Faith and enthusiasm often characterise childhood, whereas adolescence is a period of scepticism and identity-seeking (Merelman, 1972). During puberty (12 to 17 years), people are more impressionable and subject to influence. At that age, young people are increasingly conscious of their social, economic, and political environment. They start having ideological thoughts (Peterson & Somit, 1982). Impatience and willingness to change things can also characterise this period, sometimes leading to violence. Therefore, it is unsurprising that this age is the main target for recruitment in rebel groups. In Somalia, Botha and Abdile (2014) were able to conduct a study in Mogadishu. They interviewed former members of Al Shabaab, which means “the youth.” Their work showed that only 9% of interviewers joined the group after their 30s, and most joined before their 18th birthday. In West Africa, Central Mali has also been dealing with the radicalisation of its youth. Secular marginalisation and impoverishment of some parts of the population were the main drivers. Fulani nomads started in 2013 to break away from their elites, who were supposed to bridge them to the State. When realising that neither the traditional elites nor the State were doing anything tangible, people, especially youth, became permeable to the speeches of jihadist groups coming from the Tuareg rebellion (de Bruijn & Both, 2017).

The willingness of youth to join such radical groups is undeniably linked to their living standards. We, therefore, hypothesise that resentment is a crucial driver of violence. Other factors also contribute to violence. Among the most important are ethnic diversity, natural resource endowment, and the availability of infrastructures.
Firstly, ethnic diversity could undermine the provision of public goods (Habyarimana, Humphreys, Posner, & Weinstein, 2007). While some may think ethnic diversity is detrimental to economic growth, Alesina and La Ferrara (2005) suggest that ethnic diversity can be beneficial at higher levels of development. Therefore, complementarities can emerge due to ethnic diversity. One plausible explanation is that rich countries have better institutions that maintain order. They also deter ethnic conflicts or dampen their effects when they occur. However, Africa is well known for its ethnic diversity and insufficient institutional entities. The literature finds a negative impact of diversity on socioeconomic conditions that can lead to conflicts. Hence, according to Easterly and Levine (1997), highly fragmented societies are more prone to disputes, given that fragmentation reduces growth. Collier and Hoeffler (1998) disagree somehow and argue that the impact of ethnographic and linguistic fragmentation is non-linear. Therefore, very homogeneous countries have similar probabilities of conflict occurrence compared to strongly heterogeneous societies. In most cases, the conflict resides in polarised societies with a quasi-equal distribution of two ethnic groups. Indeed, in this situation, the coordination costs of rebel groups are at their minimum; hence, the risk of civil war is maximum. Montalvo and Reynal-Querol (2005) also claim that ethnic polarisation matters more than fractionalisation.

Secondly, natural resource endowment may trigger conflicts. The literature dealing with this subject is vast (see, among others: (Hinkkainen Elliott & Kreutz, 2019), (Lujala, Gleditsch, & Gilmore, 2005) (Weinstein, 2005). If the rebellion motive is secession, the endowment of a specific region in natural resources and its representation in the Government are likely to be the driving forces (Collier & Hoeffler, On the economic causes of civil wars, 1998). More precisely, the authors found that well-endowed countries have a probability of war of 0.56 against 0.12 for countries with no natural resources. However, this effect is not linear. On the one side, rebel groups are willing to capture the proceeds of the natural resource. On the other side, the financial resources of the country rise. Governments can pay for military expenditures to ensure the country's security. In subsequent work, the same authors show that the State's dependence on natural resources has a significant impact on the occurrence of separatist civil wars (Collier & Hoeffler, Greed and grievance in civil war, 2004). However, Fearon and Laitin (2003) challenged this result using the same indicator of natural resource endowment. They found no significant effect of the ratio of primary commodity exports over GDP on civil war. Other studies found mixed results (Elbadawi & Sambanis, 2002). Natural resources may have an impact. The result, however, depends on the model used (Ross, 2004). Bodea et al. (2016) eventually argue that the effect of natural wealth on conflicts is conditional on the size and the allocation of government spending, namely for welfare or the military.
Burkina Faso recently entered the club of gold producers, mainly because of industrial gold mining that started in 2008. Despite the richness of its subsoil, gold is the primary exploited resource, with 95% of exploitation by industrial companies (ITIE, 2017). Alongside industrial production, artisanal gold mining has been practised since the '80s and provides a livelihood for millions of people (Werthmann, 2017). A study by the National Institute of Statistics and Demography showed that out of the thirteen regions in the country, twelve are concerned by artisanal gold mining (INSD, 2017) and five by industrial mining (Chambre des mines, 2016). Despite the difficulty in measuring the production of artisanal gold mining sites, the INSD's study found that the production of gold was approximately 9 tons in 2016. The sector employs over a hundred and forty thousand people (Institut National de la Statistique et de la Démographie, 2017). These substantial amounts can attract some rebel groups. The International Crisis Group stated that "armed groups have been seizing gold mining sites in areas where the state is weak or absent since 2016, attracted by the boom of artisanal gold mining in the Saharan region" (International Crisis Group, 2019). According to Ouoba (2019), armed groups want to asphyxiate Sahelian countries such as Burkina Faso, Mali, and Niger and get their hands on gold mining zones. They also argue that these zones are suitable grounds for recruiting and training people for future actions (Ouoba, 2019). For example, in November 2019, a Canadian gold mining company convoy was attacked, killing 40 employees (International Crisis Group, 2019).

Thirdly, infrastructures, but more precisely, the remoteness from road infrastructures, are also key
drivers. Raleigh and Hegre (2009) assumed that civil conflicts occur in regions far from the country's
city capital in central Africa. Indeed, these regions are not easily accessible to government military
forces. When differences in local public investments cause civil conflicts, insurgencies might happen in
areas far from the city capital that attracts most of the infrastructure. Therefore, rebel groups convert
people more easily, especially the youth (Raleigh and Hegre, 2009). Similarly, Alesina and Spolaore
(2003) argue that public goods produce economies of scale so that individuals benefit from these goods
within a limited perimeter. When inhabitants live far from the main cities, they do not feel the effect
of these public goods.

4 Data and descriptive statistics

This study gathers three databases: the conflicts data of the ACLED (Armed Conflict Location and Event Data) project that provides us with our dependent variable built for 2019. The UNICEF-sponsored survey on youth conducted in 2018 allows us to construct our interest variable on youth resentment
in Burkina Faso. The MINEX database on industrial mines provides us with information regarding the
proximity of a mining site. We present descriptive statistics in Table 7 in the Appendix.

4.1 Violent events against civilians in Burkina Faso

We base this work on an essential part of the violence in Burkina Faso, which is violence against civilians involving the responsibility of armed groups. This study explicitly targets this form of violence to scrutinise better domestic violent groups, namely groups of locally recruited members. We hypothesise that “imported” violent groups preferably target political authorities represented by security forces (e.g. military or police officers) and foreigners (e.g. non-African citizens - NGO officers, tourists, foreign soldiers and official representatives, etc.). On the contrary, we assume that locally recruited groups are more likely to target civilians.<fnref n="8" />

Figure 1 shows the evolution of all events in Burkina Faso since 1997. Between 1997 and 2010, the country was almost free of violent events, except in 1998, when Norbert Zongo's assassination, who was a famous journalist, caused indignation nationwide. Protests started to rise again in 2011 with soldiers' mutiny that caused a lot of looting. Since then, protests never really go down in Burkina Faso until 2014, with the popular insurrection. The focus of this work, which is the violence against civilians, started in 2016 when armed groups began targeting Burkina Faso.

Local terrorism began to expand in 2016 in Burkina Faso, thanks to the military and training support of neighbouring countries' Katiba, which were more experienced. In fact, according to Berger (2023), AQIM and Katibat Macina contributed a lot to the establishment of a local violent extremist group, Ansarul Islam, that started its operations in 2016 with kidnapping operations. Hence, at that time, Burkina Faso became a springboard in developing that activity towards the coastal region of West Africa. The New Humanitarian<fnref n="9" /> also emphasised that the first appearance of the Islamic State in the Greater Sahara was in 2016 (Kleinfeld, 2020). When comparing the violence against civilians caused by any actor and the violence against civilians caused by armed groups, we can see that the two graphs are close. This violence reflects sexual assaults, attacks, abduction or forced disappearance, assassination, etc. The year 2019 was unprecedented when it came to this particular violence. Nearly

<footnote n="8">⁸ Of course, banditry arguably mostly hit civilians. It cannot be distinguished from terrorism; banditry and terrorism are inextricably linked. To control for the drivers of banditry, we add controls such as the Distance to Industrial Mine, Mine in the Commune, Distance to Roads and village dummies in the econometric model. We assume they capture economic conditions that foster banditry. We thank an anonymous reviewer for drawing our attention on this.</footnote>

<footnote n="9">⁹ This platform is an independent and non-profit organization.
https://www.thenewhumanitarian.org/content/about-us</footnote>
40% of events recorded are violence against civilians. In this total number, armed groups were responsible for almost three-quarters of this violence. Ethnic militia, soldiers, and police officers were involved in the other violent events.

According to the UN, terrorism in Burkina Faso increased casualties from 80 in 2016 to more than 1800 in 2019¹⁰. The number of fatalities reported by the Acled database confirms that 2019 is the deadliest one on record forces (Figure 2, panel B). The year 2019 is therefore selected to catch the spatial variability of violence.

In the 2010s, violence spread through porous frontiers in the Central Sahel region. Therefore, the violent events in Burkina Faso must be contextualised while viewing neighbouring countries, namely Mali and Niger. Map 1 and Map 2 show a concentration of violent events and attacks against civilians in zones bordering Mali and Niger. We report in Figure 3 the number of violent events against civilians and the number of fatalities. The 2010s show a surge of violence in the three countries unambiguously. We can, however, notice that violence against civilians in Burkina Faso also has some specificities. First, there was a surge of violence in 2019 in Burkina Faso and Niger compared to the previous years. Second, Burkina Faso is unique because the rise in the number of events goes along with a surge in the number of fatalities: 2019 is tragically the deadliest year on record from 1997 to 2023 in the country. Of course, we cannot rule out the porosity of borders to channel violence from Mali and Niger to Burkina Faso. Note, however, that the potential contagion will be econometrically captured by our distance variables (e.g. Distance to the nearest border – See the definition of all variables in Table 7 in the Appendix).

We do not have individual data on youth recruitment into armed groups. The only information available is the occurrence of attacks. ACLED data gather information from international, regional, national, and local reports on violent events, demonstrations, and nonviolent events (ACLED, 2019) (Raleigh, Linke, Hegre, & Karlsen, 2010). Violent events result from battles between armed and organised groups, including State forces. The counts also record violent events associated with explosive devices such as IEDs (Improvised Explosive Devices). Armed groups (State forces, rebel groups, militias) can also intentionally inflict violence on unarmed people and civilians. Demonstrations are peaceful or non-peaceful protests and riots that are somehow violent with acts such as rock-throwing and property destruction. Nonviolent actions comprise strategic development that is not associated with violent events but may trigger future violence. In Burkina Faso, this strategic

<footnote n="10">¹⁰ Interview of Mohamed Ibn Chambas, available at https://press.un.org/en/2020/sc14069.doc.htm</footnote>
development refers mainly to looting, schools and police station burning, intimidation, and tentative
abduction. <fnref n="11" />,<fnref n="12" />

Insert Figure 3 (to be found in section 8)

Map 1 presents the location of events since 1998 in Burkina Faso. Events are recorded nationwide, with a predominance of protests and riots disseminated nationwide. When focusing on violence against civilians, we can see a slight difference. Even if this type of violence outbreaks throughout the country, their perpetrators are in specific areas. Another interesting point is that most violent events are far from the cities, main road infrastructures, and homes of economic activities.

Insert map 1 (to be found in section 8)

Map 2 shows the location of violent events against civilians in 2019. We can see that violence committed by armed groups is located mainly in the northern and eastern parts of the country and near the borders the country shares with Mali and Niger.

Insert map 2 (to be found in section 8)

## 4.2 Assessing youth resentment in Burkina Faso

The second data source is a survey conducted in all thirteen regions and forty-five districts of Burkina Faso between March 22 and May 7, 2018, before the peak of violence in 2019.<fnref n="13" /> The UNICEF (United Nations Children Fund) undertook and financed this nationwide survey to assess children's physical, emotional and sexual well-being. To our knowledge, it is one of the two last national surveys before some regions became inaccessible due to insecurity.<fnref n="14" /> The survey concerns children of 0 to 17

<footnote n="11">¹¹ We rely on the ACLED database because it allows identifying the persons assaulted, namely, violence against civilians specifically. There are other sources such as the Global Terrorism Database (GTD). It rather focuses on the nature of the aggressors. Our understanding of GTD is that it seems to be more difficult to know whether attacks are targeted at civilians.</footnote>

<footnote n="12">¹² The main concern about conflict data stems from selection in reporting (Eck, 2012). Note that we add village dummies that could catch mislocation. Another concern pertains to internal validity if the catchment covers different types of conflicts that can vary over time (Raleigh, Kishi, & Linke, Political instability patterns are obscured by conflict dataset scope conditions, sources, and coding choices, 2023). However, using the year 2019 only likely minors this concern.</footnote>

<footnote n="13">¹³ The description of the survey is available in (UNICEF, 2018).</footnote>

<footnote n="14">¹⁴ The latest nationwide work on population was the National survey in December 2019. It was not able to reach all districts.</footnote>
years old. The parents<fnref n="15" /> answered questions for their 0 to 11-year-old children. Children from 12 to 17
years old responded directly to the questions with the consent of their parents. The 12-17 years
subpopulation represents 5,520 people, and 16 young people refused to sign the informed consent.
The sample, therefore, embeds 5,504 people who answered the questions. The three following
questions allow us to build 3 variables of interest:

- "Do you think your household has enough money to afford basic items such as food?"

- "Do you think your household has enough money to buy important items such as clothes, health fees, and school?"

- "Do you think your household has enough money to offer you extra items such as toys and vacation?"

Therefore, the outcome variable will be a binary variable that takes the value of 1 if the answer is yes and 0 otherwise. The youth would likely judge its situation relative to its reference group. It is, therefore, a measure of perceived relative (non)deprivation. The descriptive statistics show that most of them are satisfied with the first two items, and only 28% are satisfied with the last item.

The survey thus measures "satisfaction" in three aspects (provision of basic items regarding school, health and clothing, and provision of extra items). Figure 4 presents the share of adolescents who answered "No" to the above questions. Dissatisfaction prevail since 29%, 36% and 72% of youths declared they were not satisfied on average (Table 7 in Appendix).

More importantly, the 15 to 17-year-old group is the most pessimistic, namely that their household cannot fulfil their needs. Indeed, this group exhibits higher deprivation compared to the average. This result comforts our claim that youth resentment is critical in the violence dynamics in the country. This age group is deemed to be primarily targeted by extremist recruitment. They are also much closer to adult life and, therefore, can have a more significant potential for radicalisation. Between the three items, the majority consider their households cannot afford gifts and vacations for them.

Insert Figure 4 (to be found in section 8).

Other demographic variables include the gender index that equals 1 if the respondent is a female.
The marital status index takes the value of 1 if the adolescent has never been married and 0 otherwise.

<footnote n="15">¹⁵ In Burkina Faso, it is forbidden to ask questions directly to children under 11.</footnote>
It assesses if forced marriage is still a practice in the locality, as people of their age are not supposed to be married. This variable will also help apprehend government structures' presence and control. This explanation also holds for the inclusion of educational variables. The secondary school attendance index equals 1 if the adolescent has attended secondary school and 0 otherwise. We use the secondary school level because a 12 to 17-year-old child in Burkina Faso should typically be in secondary school. Finally, we include ethnic diversity variables relying on two indexes measured at the district (commune) level. The first one is the Ethno Linguistic Fractionalization (ELF) index widely used in the literature. ELF measures the likelihood of two randomly chosen people being from different ethnic groups (Easterly & Levine, 1997):

$$ELF = 1 - \sum_{i=1}^{N} \pi_{i}^{2} = \sum_{i}^{N} \pi_{i} (1 - \pi_{i})$$

Where $\pi_i$ is the proportion of people who belong to the ethnic group i, and N is the number of ethnic groups. When all people in a district belong to the same ethnic group, the index equals 0, making the district perfectly homogeneous. On the contrary, the district is heterogeneous when the index equals 1. Though Burkina Faso counts more than 60 ethnic groups, 10 ethnolinguistic groups only are accounted for in surveys. The average value of the indicator is 0.30, which means that districts are somewhat fragmented in terms of ethnicity.

Following Montalvo and Reynal-Querol (2005), we also compute the polarisation index POL as follows:

$$1 - \sum_{i=1}^{N} \left( \frac{\frac{1}{2} - \pi_{i}}{\frac{1}{2}} \right)^{2} \pi_{i}$$

The index captures the fact that a district comprises two ethnic groups, which is the underlying fuel for conflicts. The difference with the fractionalisation index is that the former will increase and be near 1 when almost all people in the district are of different ethnic groups. The latter will nearly be equal to 1 when a district comprises two ethnic groups, each with 50% of the population (Mavridis, 2015). Using this index, Montalvo and Reynal-Querol (2005a) found that ethnic polarisation exacerbates conflicts. This index better explains conflicts than the fractionalisation index (Mavridis, 2015).
## 4.3 Mining activities and road network

We draw on a third database from MinEX Consulting on industrial mines. Several variables allow us to disentangle the role of natural resource endowments as drivers of violence. MinEX Consulting estimates that the database covers 99% of worldwide giant-sized deposits, 95% of major deposits, 70% of moderate ones, and 50% of minor deposits since 1950 (Ahlerup, Baskaran, & Bigsten, 2019). The database reports information such as the geographical location (longitude and latitude coordinates) and size of the site, the discovery year, the mine startup year, the nature of the ore exploited, and the exploitation statuses. In Burkina Faso, five industrial gold mines have been effectively operating between 2011 and 2013. According to the mining law in Burkina Faso, companies are granted an exploitation permit for 20 years. It is renewable every five years until the depletion of the ore.<fnref n="16" />

Lastly, using geographically localised information (latitude and longitude coordinates) on the road network, we compute the distances to borders and two types of roads: trunk and primary roads. Trunk roads are found mainly in cities such as the political capital, namely Ouagadougou. Primary roads are national roads generally leading to rural areas. Those two variables proxy the location's distance and remoteness to the central political power. We compute these two variables while taking the distance from the centroid of a specific location to the roads. We also calculate distances to the nearest border using the main practicable roads to compute the exact distance to reach the border.<fnref n="17" />

# 5 Econometric analysis

Our dependent variable counts the number of violent events by district or “communes” in 2019, suggesting a count regression strategy. The Poisson estimator is not relevant. Indeed, one crucial assumption of this estimator is that the mean of the dependent variable is equal to its variance. This assumption does not hold in our case because the mean is 1.32 while the variance is 19.38. We then resort to using the negative binomial regression deemed more suitable for over-dispersed data. The likelihood ratio test of the specification's dispersion parameter (alpha) significantly differs from 0,

<footnote n="16">¹⁶ In Burkina Faso, TAPARKO (Centre Nord), BOMBORE (Plateau central), YOUGA (Centre Est), and INATA (Sahel) are major size deposits (deposits superior or equal to 2.24 million of ounces). ESSAKANE (Sahel) and MANA (Boucle du Mouhoun) are classified as giant size gold deposits (deposits superior or equal to 11.18 million of ounces).</footnote>

<footnote n="17">¹⁷ Burkina Faso shares borders with Mali, Niger, Ivory Coast, Ghana, the Republic of Benin and Togo.</footnote>
corroborating our choice. Moreover, we control unobservable spatial heterogeneity with village-fixed effects.<fnref n="18" />

We present first our main results in section 0. Section 5.2, on the one hand, highlights some heterogeneities according to different age groups and gender and, on the other hand, focuses on potential complementarities between satisfaction motives. Although the possibility of an endogeneity bias cannot be completely ruled out, several indications suggest that the risk is moderate. First, we control by village fixed effects and several variables that likely affect youth resentment and conflicts. Second, there is no reason to believe that the conflicts of 2019, unprecedented in both scale and nature, should influence the youth resentment recorded in 2018. We do not claim "Post hoc ergo propter hoc" but consider it reasonably mitigates reverse causality. Reverse causality concern would be more plausible in the case of inertia in violence, namely if the violent events had the same intensity in 2018 and 2019, which is not the case. Third, reasoning by the absurd leads us to point out that if the violence before 2019 had been so great, the survey would not have been able to take place for obvious reasons of the safety of the surveyors, who are often perceived as representatives of the authorities. Nevertheless, given the lack of valid instruments, the results can only be interpreted as causal relationships with the necessary caution.

## 5.1 Main results

Table 1 reports our baseline results relying on the negative binomial estimator. They show that youth satisfaction towards the three items cited above is negatively correlated with the occurrence of violent events in 2019. Since the interest variable is a dummy variable, the marginal effects provide a straightforward measure of the impact of deprivation on the number of violent events. Being satisfied concerning basic items (Satisfaction_1) decreases the number of violent events by 1.16 or 1.15 (right part of the table). The orders of magnitudes are pretty similar. We can compare the marginal effects to the average number of events (1.33). Deprivation roughly doubles the number of events on average or represents one-fourth of the standard deviation (4.42).

<footnote n="18">¹⁸ Given the important number of zeros reported for the dependent variable, we could have used zero-inflated regression models. However, it was difficult to find an adequate variable to make a distinction between “real peace” in the commune, and a “fake peace” because the event was not reported. Existing studies analysing the determinants of conflicts with zero-inflated regression models use cross-country database where disentangling fake and real events seems making more sense (Dunne & Tian, 2016). In addition, there is no consensus on using zero-inflated models (see e.g. the debate between Allison and Greene https://statisticalhorizons.com/zero-inflated-models acceded May 29th, 2020.</footnote>
Of course, this result does not mean that most discontented young men do actually join rebel groups. On the one hand, the lack of data on recruitment makes it impractical to claim that. On the other hand, participation in an armed group is a kind of “public good” and is subject to the free-rider or Olson’s paradox of collective action (Olson, 1971). Hence, many discontented young people will decide not to act violently.

Insert Table 1 (to be found in section 9)

Moreover, when the commune is highly polarised, this has a very significant impact on conflicts. The table also reports the results using two different measures of ethnic diversity, namely polarisation (POL) and Ethno Linguistic Fractionalization (ELF). Both have the expected positive effect on the occurrence of violence. This result may seem surprising in the case of Burkina Faso. However, the actions of terrorist groups may exacerbate ethnic tensions, fueling mistrust between communities.<fnref n="19" />

When introducing variables on mining activities (table 2), we can see that an industrial mine in the commune positively impacts the occurrence of conflicts by approximately 2 counts. As an alternative measure to the presence of mines, we introduce the distance to the nearest mine site (table 2), which still has a positive effect, though it is less significant and of lower magnitude. This result is interesting since, on average, the nearest industrial mine is 72 kilometres away from the commune, which is close. Therefore, the proximity of the industrial mine goes beyond its actual establishment in the commune. It expands to its geographical proximity. In Burkina Faso, artisanal gold mining is widespread and develops around industrial gold mining sites. As stated in section 3, armed groups target them to capture their proceeds. The distance to the industrial mine distance can also somehow capture artisanal gold mining sites.

Insert table 2 (to be found in section 9)

The proximity to borders favours the action of armed groups (Table 3). In these areas, they coordinate better and fall back in the nearest countries, especially in Mali and Niger, where the borders with Burkina Faso are blurred. Violence spillovers originating from neighbouring countries are also consistent with the positive effect of the Distance to the border variable. The distance to the “trunk” road type has a positive effect, contrary to the “primary” road type. We interpret both as remoteness from cities and infrastructures. In fact, for the former, the result shows that the remoteness of highway roads, mainly found in the main cities, positively impacts conflicts, which is understandable. The latter

<footnote n="19">¹⁹ Note that we replicate our baseline model using the Global Terrorism Database to count violent attacks against civilians. Results are unchanged except the Satisfaction_2 variable that is not significant. The results are provided in Table 8 in Appendix.</footnote>
has a negative effect, meaning conflicts are more frequent when the commune lies near primary roads.
We explain this result as follows. Primary roads are mainly found in rural areas and are often of poor
quality due to potholes, where armed groups place IEDs. In brief, these results emphasise that violent
conflicts are more frequent in rural (remote) areas and less frequent in the main cities, where security
forces are more likely to counteract armed groups' intrusions. They are consistent with the recent
UNDP report that underlined "state disintegration" and institutions "confined to urban and suburban
zones" of Burkina Faso (United Nations Development Programme, 2023).<fnref n="20" />

Insert table 3 (to be found in section 9)

5.2 Heterogeneity analysis

We investigate here the heterogeneous effect of satisfaction according to the age of the respondents. The coefficients of the age group between 15 and 17 years are the highest whatever the question. The satisfaction of the oldest individuals has a higher impact on conflicts, presumably because they are the preferred targets of armed group recruiters (Table 4).

Insert Table 4 (to be found in Section 9)

Table 5 then presents complementarities between the different indices of youth satisfaction. We think that satisfied people in two separate items will be even less prone to violent action.

Insert Table 5 (to be found in Section 9)

Table 6 presents the results regarding the subpopulation of males and females. We show that the impact of these different satisfactions is higher for male youth than for females, other things held equal. We understand this result as armed groups preferably recruit young males. Females are less engaged in these activities; when they are, they are not primarily recruited as fighters.

Insert Table 6 (to be found in Section 9)

6 Concluding remarks

Our study contributes to substantive literature on the socioeconomic determinants of violent
domestic conflicts (see. e.g. (Vijaya, Wilent, Cathcart, & Fiorellini, 2018). We focus on Burkina Faso

<footnote n="20">²⁰ Note that Mining and distance variables also control for the drivers of banditry which often take the form of violence against civilians.</footnote>
since “the surge in violent extremism in sub-Saharan Africa undermines hard-won development gains and threatens to hold back progress for generations to come.” (United Nations Development Programme, 2023). Burkina Faso has been making international headlines these past years because of the terrorist context the country has known. There are many lines and military expenditures, but the fight is not over. A military solution alone seems not to be adequate for the situation, as stated by Bakary Sambe:

“Military solutions have not been successful in the fight against terrorism in the Sahel. The lessons of America’s war in Afghanistan should have forced the international community to face facts: Kalashnikovs alone cannot defeat ideology nor solve the structural problems feeding the radicalisation of the young people who continue to join Boko Haram and the Islamic State in the Greater Sahara.” (Sambe, 2019).

We address these structural problems in this paper. We focus this study on the role played by economic grievances and relative deprivation perceived by youths. We argue that youth resentment towards the ability of their households to fulfil several needs is a crucial determinant of the occurrence of violence in their districts. Results show that wherever young people were satisfied with the ability of their households to afford food, education, clothes, and other extra items in 2018, it lowered the probability of an attack against civilians in 2019. This result is more noticeable when young people are in the 15-17 age group, a crucial period in children's development. It also highlights the importance of considering the feelings of young people towards their living conditions to avoid their radicalisation.

Our results hold while considering other drivers. They are the presence of industrial mines in the vicinity, the ethnic fractionalisation and polarisation, the remoteness from the cities, and the proximity of the borders with countries characterised by insecurity. These other factors imply looking at the terrorist phenomenon in Burkina Faso from several angles, even if the role of living conditions is essential. A limitation of the study is that we cannot definitely rule out an endogeneity bias since our data only allow us to take advantage of the spatial variability of youth resentment as measured by the 2018 UNICEF survey.

Therefore, the fight against terrorism in the Sahel requires implementing repressive and preventive policies. This recommendation is even stronger in Burkina Faso and other Sahelian countries, of which adolescents and young adults represent more than 30% of the country's population. The aim is to dry up recruitment sources for terrorist groups by improving young people's material and psychological
situation. Education is one way of doing this alongside development projects targeting young people.<fnref n="21" />
In addition, a targeted youth employment policy must be a priority for national governments.<fnref n="22" /> It is,
therefore, essential to encourage policies that aim to invest in remote areas and reinforce the sense
of belonging of young citizens to their homeland. All these initiatives are part of a broader project
aiming to enhance young adults' and adolescents' health and well-being (Patton, et al., 2016).

<footnote n="21">²¹ See for instance, the Positive Youth Development framework.</footnote>

<footnote n="22">²² See for instance, the recent statements issued by the United Nations Security Council on counter-terrorism in Africa: https://www.un.org/press/en/2020/sc14140.doc.htm</footnote>
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8 Figures and maps

<figure><img src="image_1.png" /><figcaption>Figure 1. Evolution of violent events in Burkina Faso</figcaption></figure>

Source: ACLED Database and author's calculations.
<caption>Figure 2. Violence against civilians and Protests and riots in Burkina Faso</caption>

Panel A: Events count

<figure><img src="image_2.png" /></figure>

Panel B: Fatalities count

<figure><img src="image_3.png" /></figure>
<caption>Figure 3. Violence against civilians in Burkina Faso, Mali and Niger</caption>

<figure><img src="image_4.png" /><figcaption>Panel B</figcaption></figure>

<figure><img src="image_5.png" /></figure>

Source: Source: ACLED Database and author's calculations
<figure><img src="image_6.png" /><figcaption>Map 1. Location of violent events in Burkina Faso since 1998</figcaption></figure>

Source: ACLED data, OpenStreetMap data, FieldMaps data, and authors' calculations.
<figure><img src="image_7.png" /><figcaption>Map 2. Location of violent events against civilians and their authors in 2019</figcaption></figure>

Source: ACLED Data, OpenStreetMap data, FieldMaps data, and authors' calculations
<figure><img src="image_8.png" /><figcaption>Figure 4. Youth resentment in Burkina Faso in 2018</figcaption></figure>

"Do you think your household has enough money to afford basic items such as food?"

"Do you think your household has enough money to buy essential items such as clothes, health, and school fees?"

"Do you think your household has enough money to offer you extra items such as toys and vacation?"

Source: Authors' calculations from the 2018 survey on violence against children in Burkina Faso
## 9 Econometric results

Unless otherwise stated, the dependent variable is the number of violent attacks against civilians as reported in the ACLED database. All econometric models are run with village-fixed effects.

<table><caption>Table 1. Determinants of violent events – Marginal effects - Baseline negative binomial estimator</caption><thead><tr><th></th><th></th><th></th><th></th></tr></thead><tbody><tr><td>Satisfaction_1</td><td>-1.160 ***<br>(0.032)</td><td></td><td>-1.153***<br>(0.032)</td></tr><tr><td>Satisfaction_2</td><td></td><td>-1.195***<br>(0.040)</td><td>-1.191***<br>(0.041)</td></tr><tr><td>Satisfaction_3</td><td></td><td></td><td>-1.04***<br>(0.068)</td></tr><tr><td>POL</td><td>3.791***<br>(0.260)</td><td>3.809***<br>(0.254)</td><td>3.837***<br>(0.261)</td></tr><tr><td>ELF</td><td></td><td></td><td>3.609***<br>(0.268)</td></tr><tr><td>Marital_Status</td><td>-1.269 **<br>(0.029)</td><td>-1.284**<br>(0.029)</td><td>-1.269**<br>(0.029)</td></tr><tr><td>Secondary_status</td><td>-1.230 ***<br>(0.038)</td><td>-1.251**<br>(0.038)</td><td>-1.264**<br>(0.041)</td></tr><tr><td>R.Squared</td><td>0.367</td><td>0.364</td><td>0.349</td></tr><tr><td>Observations</td><td>5,331</td><td>5,323</td><td>5,331</td></tr></tbody></table>

Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1
<table><caption>Table 2. Determinants of violent events with mining activities– Marginal effects - Negative binomial estimator</caption><thead><tr><th></th><th></th><th></th><th></th></tr></thead><tbody><tr><td>Satisfaction_1</td><td>-1.157***<br>(0.032)</td><td></td><td>-1.168***<br>(0.033)</td></tr><tr><td>Satisfaction_2</td><td></td><td>-1.192***<br>(0.041)</td><td>-1.204***<br>(0.041)</td></tr><tr><td>Satisfaction_3</td><td></td><td></td><td>-0.980***<br>(0.062)</td></tr><tr><td>Industrial Mine</td><td>2.151***<br>(0.340)</td><td>2.096***<br>(0.327)</td><td>2.271***<br>(0.363)</td></tr><tr><td>Log (Distance to mine)</td><td></td><td></td><td>0.102*<br>(0.0530)</td></tr><tr><td>Polarisation</td><td>3.783***<br>(0.262)</td><td>3.804***<br>(0.256)</td><td>3.782***<br>(0.256)</td></tr><tr><td>Marital Status</td><td>-1.271**<br>(0.029)</td><td>-1.286**<br>(0.029)</td><td>-1.273**<br>(0.029)</td></tr><tr><td>Secondary_status</td><td>-1.231***<br>(0.039)</td><td>-1.251**<br>(0.039)</td><td>-1.232**<br>(0.039)</td></tr><tr><td>R.Squared</td><td>0.3679</td><td>0.3644</td><td>0.3648</td></tr><tr><td>Observations</td><td>5,331</td><td>5,323</td><td>5,084</td></tr></tbody></table>

Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1
<table><caption>Table 3. Determinants of violent events with mining activities and distance to borders and roads – Marginal effects - Negative binomial estimator</caption><thead><tr><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th></tr></thead><tbody><tr><td>Satisfaction_1</td><td>- 1.163***<br>(0.0766)</td><td></td><td>-1.159***<br>(0.0829)</td><td></td><td></td><td>-1.164***<br>(0.0762)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Satisfaction_2</td><td></td><td>-1.178***<br>(0.0728)</td><td></td><td>-1.201***<br>(0.0803)</td><td></td><td></td><td>-1.184***<br>(0.0737)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Satisfaction_3</td><td></td><td></td><td>- 1.021***<br>(0.0815)</td><td></td><td>-0.982***<br>(0.0852)</td><td></td><td></td><td>-1.085***<br>(0.0785)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Industrial Mine</td><td>2.315***<br>(0.156)</td><td>2.318***<br>(0.156)</td><td>2.399***<br>(0.155)</td><td>1.762*<br>(0.167)</td><td>1.715<br>(0.165)</td><td>1.876**<br>(0.169)</td><td>5.377***<br>(0.171)</td><td>5.376***<br>(0.169)</td><td>5.107***<br>(0.165)</td><td></td><td></td><td></td><td></td></tr><tr><td>Polarisation</td><td>2.823***<br>(0.301)</td><td>2.810***<br>(0.293)</td><td>2.873***<br>(0.299)</td><td>4.062***<br>(0.251)</td><td>4.074***<br>(0.247)</td><td>4.104***<br>(0.255)</td><td>4.368***<br>(0.314)</td><td>4.362***<br>(0.300)</td><td>4.338***<br>(0.312)</td><td></td><td></td><td></td><td></td></tr><tr><td>Marital status</td><td>-1.272*<br>(0.0876)</td><td>-1.293<br>(0.0988)</td><td>-1.277*<br>(0.0883)</td><td>-1.275**<br>(0.127)</td><td>-1.288**<br>(0.129)</td><td>-1.284**<br>(0.117)</td><td>-1.284**<br>(0.0838)</td><td>-1.300*<br>(0.0843)</td><td>-1.281**<br>(0.0781)</td><td></td><td></td><td></td><td></td></tr><tr><td>Secondary level</td><td>-1.231**<br>(0.0640)</td><td>-1.254**<br>(0.0637)</td><td>-1.248*<br>(0.0653)</td><td>- 1.239***<br>(0.0704)</td><td>- 1.259**<br>(0.0700)</td><td>-1.264**<br>(0.0705)</td><td>- 1.236**<br>(0.0621)</td><td>-1.256**<br>(0.0614)</td><td>- 1.247**<br>(0.0631)</td><td></td><td></td><td></td><td></td></tr><tr><td>Logens distance to border)</td><td>-0.322***<br>(0.0315)</td><td>-0.323***<br>(0.0317)</td><td>-0.306***<br>(0.0317)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Logens distance to primary roads)</td><td></td><td></td><td></td><td>-0.131***<br>(0.0372)</td><td>-0.127***<br>(0.0370)</td><td>-0.126***<br>(0.0376)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Logens distance to trunk roads)</td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.300***<br>(0.0331)</td><td>0.305***<br>(0.0328)</td><td>0.283***<br>(0.0325)</td><td></td><td></td><td></td><td></td></tr><tr><td>R.squared</td><td>0.3843</td><td>0.3808</td><td>0.3796</td><td>0.3698</td><td>0.3662</td><td>0.3666</td><td>0.3849</td><td>0.3819</td><td>0.3796</td><td></td><td></td><td></td><td></td></tr><tr><td>Observations</td><td>5,331</td><td>5,323</td><td>5,084</td><td>5,331</td><td>5,323</td><td>5,084</td><td>5,331</td><td>5,323</td><td>5,084</td><td></td><td></td><td></td><td></td></tr></tbody></table>

Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1.
<table><caption>Table 4. Determinants of violent events depending on the age of the respondents – Marginal effects - Negative binomial estimator</caption><tbody><tr><td>Satisfaction_1_12_14</td><td>-1.09***<br>(0.108)</td></tr><tr><td>Satisfaction_1_15_17</td><td>-1.23***<br>(0.114)</td></tr><tr><td>Satisfaction_2_12_14</td><td>-1.13**<br>(0.0993)</td></tr><tr><td>Satisfaction_2_15_17</td><td>-1.22***<br>(0.118)</td></tr><tr><td>Satisfaction_3_12_14</td><td>-0.93***<br>(0.113)</td></tr><tr><td>Satisfaction_3_15_17</td><td>-1.08**<br>(0.137)</td></tr><tr><td>Industrial Mine</td><td>2.08***<br>(0.191)</td><td>2.55**<br>(0.268)</td><td>2.08***<br>(0.192)</td><td>2.60**<br>(0.264)</td><td>2.12***<br>(0.195)</td><td>2.70**<br>(0.255)</td></tr><tr><td>Polarisation</td><td>3.197***<br>(0.501)</td><td>2.595***<br>(0.382)</td><td>3.073***<br>(0.468)</td><td>2.623***<br>(0.387)</td><td>3.208***<br>(0.469)</td><td>2.613***<br>(0.401)</td></tr><tr><td>Marital status</td><td>-1.19<br>(0.0790)</td><td>-1.34**<br>(0.116)</td><td>-1.23<br>(0.0674)</td><td>-1.33*<br>(0.137)</td><td>-1.20<br>(0.0706)</td><td>-1.33**<br>(0.121)</td></tr><tr><td>Secondary status</td><td>-1.06**<br>(0.0911)</td><td>-1.39<br>(0.111)</td><td>-1.11**<br>(0.0884)</td><td>-1.40<br>(0.116)</td><td>-1.08**<br>(0.0902)</td><td>-1.40<br>(0.118)</td></tr><tr><td>Log (Distance to border)</td><td>-0.384***<br>(0.0410)</td><td>-0.243***<br>(0.0475)</td><td>-0.383***<br>(0.0408)</td><td>-0.248***<br>(0.0492)</td><td>-0.355***<br>(0.0411)</td><td>-0.243***<br>(0.0493)</td></tr><tr><td>R. Squared</td><td>0.39</td><td>0.37</td><td>0.39</td><td>0.37</td><td>0.39</td><td></td></tr><tr><td>Observations</td><td>2,933</td><td>2,398</td><td>2,931</td><td>2,392</td><td>2,786</td><td>2,298</td></tr></tbody></table>

Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1
<table><caption>Table 5. Determinants of violent events testing complementarities with satisfaction motives - – Marginal effects - Negative binomial estimator</caption><tbody><tr><td>Satisfaction_total</td><td>-0.99***<br>(0.117)</td><td></td><td></td></tr><tr><td>Satisfaction_1_2</td><td></td><td>-1.08***<br>(0.0924)</td><td></td></tr><tr><td>Satisfaction_1_3</td><td></td><td></td><td>-0.92***<br>(0.112)</td></tr><tr><td>Industrial Mine</td><td>2.26**<br>(0.238)</td><td>2.48***<br>(0.175)</td><td>2.46***<br>(0.240)</td></tr><tr><td>Polarisation</td><td>2.726***<br>(0.397)</td><td>2.845***<br>(0.332)</td><td>2.763***<br>(0.375)</td></tr><tr><td>Marital status</td><td>1.26<br>(0.116)</td><td>-1.21<br>(0.0936)</td><td>-1.26<br>(0.165)</td></tr><tr><td>Secondary status</td><td>-1.22<br>(0.0881)</td><td>-1.17**<br>(0.0742)</td><td>-1.23<br>(0.0913)</td></tr><tr><td>Log (Distance to border)</td><td>-0.300***<br>(0.0415)</td><td>-0.322***<br>(0.0349)</td><td>-0.311***<br>(0.0396)</td></tr><tr><td>R. Squared</td><td>0.39</td><td>0.38</td><td>0.39</td></tr><tr><td>Observations</td><td>2,945</td><td>4,590</td><td>2,839</td></tr></tbody></table>

Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1.
<table><caption>Table 6. Determinants of violent events testing gender effects - Marginal effects - Negative binomial estimator</caption><tbody><tr><td>Satisfaction_1</td><td>-1.224***<br>(0.0976)</td><td>-1.102***<br>(0.125)</td><td></td><td></td><td></td><td></td></tr><tr><td>Satisfaction_2</td><td></td><td></td><td>-1.237***<br>(0.0959)</td><td>-1.111**<br>(0.114)</td><td></td><td></td></tr><tr><td>Satisfaction_3</td><td></td><td></td><td></td><td></td><td>-1.042***<br>(0.114)</td><td>-0.966**<br>(0.125)</td></tr><tr><td>Industrial Mine</td><td>3.474***<br>(0.273)</td><td>1.873**<br>(0.193)</td><td>3.433***<br>(0.279)</td><td>1.864**<br>(0.189)</td><td>3.884***<br>(0.272)</td><td>1.855*<br>(0.185)</td></tr><tr><td>Polarisation</td><td>2.405***<br>(0.428)</td><td>3.152***<br>(0.419)</td><td>2.390***<br>(0.420)</td><td>3.147***<br>(0.410)</td><td>2.360***<br>(0.418)</td><td>3.313***<br>(0.432)</td></tr><tr><td>Marital status</td><td>-1.334<br>(0.190)</td><td>-1.163**<br>(0.125)</td><td>-1.371<br>(0.180)</td><td>-1.157*<br>(0.143)</td><td>-1.354<br>(0.152)</td><td>-1.144**<br>(0.134)</td></tr><tr><td>Secondary level</td><td>-1.308<br>(0.0877)</td><td>-1.116**<br>(0.107)</td><td>-1.333<br>(0.0867)</td><td>-1.139*<br>(0.105)</td><td>-1.315<br>(0.0906)</td><td>-1.153<br>(0.105)</td></tr><tr><td>Logens distance to border)</td><td>-0.403***<br>(0.0437)</td><td>-0.248***<br>(0.0464)</td><td>-0.407***<br>(0.0430)</td><td>-0.245***<br>(0.0472)</td><td>-0.399***<br>(0.0436)</td><td>-0.217***<br>(0.0470)</td></tr><tr><td>Gender_M</td><td>Yes</td><td>No</td><td>Yes</td><td>No</td><td>Yes</td><td>No</td></tr><tr><td>Gender_F</td><td>No</td><td>Yes</td><td>No</td><td>Yes</td><td>No</td><td>Yes</td></tr><tr><td>R.squared</td><td>0.4037</td><td>0.3723</td><td>0.4024</td><td>0.3672</td><td>0.3983</td><td>0.3690</td></tr><tr><td>Observations</td><td>2,814</td><td>2,517</td><td>2,813</td><td>2,510</td><td>2,700</td><td>2,384</td></tr></tbody></table>

Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1.
10 Appendix

<table><caption>Table 7. Descriptive statistics</caption><thead><tr><th>Variable name</th><th>Nb Obs.</th><th>Description</th><th>Mean</th><th>St.Dev</th><th>Min</th><th>Max</th><th>Source</th></tr></thead><tbody><tr><td>Violent Conflicts</td><td>354</td><td>Nb of conflicts</td><td>1.33</td><td>4.42</td><td>0</td><td>33</td><td>ACLED Database (2019). See (Raleigh, Linke, Hegre, & Karlsen, 2010)</td></tr><tr><td>Violent Conflicts</td><td>354</td><td>Nb of conflicts</td><td>0.11</td><td>0.55</td><td>0</td><td>4</td><td>Global Terrorism Database. (START (National Consortium for the Study of Terrorism and Responses to Terrorism), 2022)</td></tr><tr><td>Satisfaction_1<br>Of which:<br>12_14 year-olds</td><td>5,331</td><td>Equals 1 if the young person is satisfied regarding basic items</td><td>0.71</td><td>0.45</td><td>0</td><td>1</td><td>UNICEF Survey (2018). See (UNICEF, 2018)</td></tr><tr><td>Satisfaction_1<br>Of which:<br>15_17 year-olds</td><td>2,933</td><td>Equals 1 if the young person is satisfied regarding basic items</td><td>0.72</td><td>0.45</td><td>0</td><td>1</td><td>UNICEF Survey (2018)</td></tr><tr><td>Satisfaction_2<br>Of which:<br>12_14</td><td>5,323</td><td>Equals 1 if the young person is satisfied regarding essential items (school health and clothing)</td><td>0.64</td><td>0.48</td><td>0</td><td>1</td><td>UNICEF Survey (2018)</td></tr><tr><td>Satisfaction_2<br>Of which:<br>15_17</td><td>2,931</td><td>Equals 1 if the young person is satisfied regarding essential items (school health and clothing)</td><td>0.65</td><td>0.48</td><td>0</td><td>1</td><td>UNICEF Survey (2018)</td></tr><tr><td>Satisfaction_3<br>Of which:<br>12_14</td><td>5,084</td><td>Equals 1 if the young person is satisfied regarding extra items like gifts</td><td>0.28</td><td>0.45</td><td>0</td><td>1</td><td>UNICEF Survey (2018)</td></tr><tr><td>Satisfaction_3<br>Of which:<br>15_17</td><td>2,786</td><td>Equals 1 if the young person is satisfied regarding extra items like gifts</td><td>0.28</td><td>0.45</td><td>0</td><td>1</td><td>UNICEF Survey (2018)</td></tr><tr><td>Satisfaction_total</td><td>2,945</td><td>Equals 1 if the young person is satisfied according to the three types of goods</td><td>0.55</td><td>0.49</td><td>0</td><td>1</td><td>UNICEF Survey (2018)</td></tr><tr><td>Satisfaction_1_2</td><td>4,590</td><td>Equals 1 if the young person is satisfied according to goods basic and essential items</td><td>0.70</td><td>0.49</td><td>0</td><td>1</td><td>UNICEF Survey (2018)</td></tr><tr><td>Satisfaction_1_3</td><td>2,839</td><td>Equals 1 if the young person is satisfied according to basic and extra items</td><td>0.49</td><td>0.50</td><td>0</td><td>1</td><td>UNICEF Survey (2018)</td></tr></tbody></table>
<table><tr><td>Gender_M</td><td>2,900</td><td>Equals 1 if the young person is Male</td><td>0.53</td><td>0.50</td><td>0</td><td>1</td><td>UNICEF Survey (2018)</td></tr><tr><td>Gender_F</td><td>2,604</td><td>Equals 1 if the young person is Female</td><td>0.47</td><td>0.50</td><td>0</td><td>1</td><td>UNICEF Survey (2018)</td></tr><tr><td>Industrial mine</td><td>5,504</td><td>Equals 1 if there is an industrial mining site in the commune</td><td>0.24</td><td>0.15</td><td>0</td><td>1</td><td>MINEX Database (Operating mines that started in 2007, 2008 and 2010)</td></tr><tr><td>Marital status</td><td>5,504</td><td>Equals 1 if the young person was never married</td><td>0.98</td><td>0.15</td><td>0</td><td>1</td><td>UNICEF Survey (2018)</td></tr><tr><td>Secondary level</td><td>5,504</td><td>Equals 1 if the young person ever attended secondary school</td><td>0.62</td><td>0.48</td><td>0</td><td>1</td><td>UNICEF Survey (2018)</td></tr><tr><td>Distance to border</td><td>5,504</td><td>Distance to the nearest border (kilometres)</td><td>98.22</td><td>68.43</td><td>0</td><td>249.51</td><td>UNICEF Survey and OpenstreetMap Data (2018)</td></tr><tr><td>Distance to trunk roads</td><td>5,504</td><td>Distance to the nearest "trunk" type road (kilometres)</td><td>66.94</td><td>74.03</td><td>0</td><td>315.67</td><td>UNICEF Survey and OpenStreetMap Data (2018)</td></tr><tr><td>Distance to primary roads</td><td>5,504</td><td>Distance to the nearest road type "primary" (kilometres)</td><td>15.37</td><td>21.76</td><td>0</td><td>118.73</td><td>UNICEF Survey and OpenStreetMap Data (2018)</td></tr><tr><td>Distance to Mine</td><td>5,504</td><td>Distance to the nearest industrial Mine (kilometres)</td><td>72.87</td><td>43.87</td><td>0</td><td>248.06</td><td>UNICEF Survey and MINEX Data (2018)</td></tr><tr><td>Fractionalization or ELF</td><td>5,504</td><td>Fractionalisation of ethnic groups index</td><td>0.30</td><td>0.25</td><td>0</td><td>0.81</td><td>UNICEF Survey (2018)</td></tr><tr><td>Polarisation or POL</td><td>5,504</td><td>Polarisation of ethnic groups index</td><td>0.43</td><td>0.32</td><td>0</td><td>1</td><td>UNICEF Survey (2018)</td></tr></table>
<table><caption>Table 8. Determinants of violent events – Marginal effects - Baseline negative binomial estimator using the Global Terrorism Database to count the violent attacks against civilians</caption><tr><td>Satisfaction_1</td><td>-0.103***<br>(0.097)</td><td></td><td></td></tr><tr><td>Satisfaction_2</td><td></td><td>-0.115<br>(0.083)</td><td></td></tr><tr><td>Satisfaction_3</td><td></td><td></td><td>-0.075***<br>(0.107)</td></tr><tr><td>POL</td><td>3.869***<br>(0.412)</td><td>4.009***<br>(0.432)</td><td>4.420***<br>(0.478)</td></tr><tr><td>Marital_status</td><td>-0.1130**<br>(0.138)</td><td>-0.1157**<br>(0.136)</td><td>-0.123**<br>(0.157)</td></tr><tr><td>Secondary_status</td><td>-0.109*<br>(0.079)</td><td>-0.113*<br>(0.078)</td><td>-0.113*<br>(0.078)</td></tr><tr><td>Village fixed effects</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>R.Squared</td><td>0.528</td><td>0.528</td><td>0.532</td></tr><tr><td>Observations</td><td>5,331</td><td>5,323</td><td>5,084</td></tr></table>

Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1.

In the GTD database, it is difficult to know whether attacks targeted civilians. For 2019 and concerning civilians, there were attacks against: -Businesses, Educational institutions, Government representations, NGOs, Private goods, Religious and institutional people, Tourists, Transportation actors, Public services, Other. These attacks can take the form of damage to property or direct violence against civilians themselves.