Over the past ten years, the question of whether violent conflicts are the result of genuine grievances or the product of an environment in which rebellion is an attractive and/or viable option has been at the heart of a fierce theoretical controversy known as the greed versus grievance debate. The debate was sparked when Paul Collier and Anke Hoeffler claimed that rebellion cannot be explained by grievances resulting from ethnic animosities or economic and political inequalities, because situations in which people want to rebel are ubiquitous, whereas the circumstances in which people are able to rebel (weak states, rough terrain, the presence of lootable resources etc.) are sufficiently rare to constitute the explanation.
This claim and its morally charged phrasing in terms of “greed” and “grievance” posed a tough challenge to the dominant view of many political scientists and to conventional wisdom more generally. While many scholars subsequently shifted their attention to studying the opportunities for conflict, others put their efforts into finding better ways to measure people’s grievances. An award-winning book on Inequality, Grievances, and Civil War, published in 2013, testifies to the fact that the jury in this debate is still out.
Taking a Step Back
In a recently published article in the Journal of Peace Research, I took a step back and argued that the question of whether incentive- or opportunity-based explanations of conflict have more explanatory power is misguided. It seems common sense that people and groups need to be both willing and able to rebel, and conflict is thus likely the result of a complex interaction of both grievances and opportunities. This opens up a new question that is arguably more fruitful than the ‘either-or’ framing of the debate so far: How do incentives and opportunities interact in leading to violent conflict?
In the social world, certain phenomena tend to cluster together because they are interrelated (think poverty and educational achievement). This confounded nature of the social world is also known as „limited diversity.“ [1] From this follows that although there could technically be hundreds of ways in which grievances and opportunity structures interact to lead to violent conflict, certain grievances and opportunities may be causally linked and reinforce each other. If this is the case, we should be able to find certain constellations of risk factors that are particularly conducive to rebellion. Detecting these constellations among a set of 500 periods of ethnic conflict and peace between 1990 and 2009 was the purpose of my study.
The challenge was that mainstream quantitative methods in conflict research are well-suited to test competing explanations against each other, but ill-suited to demonstrate the complex interplay of risk factors. I thus employed Qualitative Comparative Analysis (QCA), a method that lends itself to the identification of complex patterns or constellations of risk factors and map multiple paths to the same outcome.
Four Patterns
The most striking finding of this analysis is that no more than four different patterns reliably explain the onset of almost two-thirds of all ethnic conflicts between 1990 and 2009. Appropriating some of the field’s well-known catchphrases, I labeled them accordingly:
The “conflict trap” pattern is by far the most common. If an ethnic group was already involved in rebellion over the past ten years and is still politically excluded, then conflict tends to break out with a high consistency. In this situation, a current grievance (political exclusion) is coupled with a situation in which a previous conflict may have left both emotional scars and a legacy of conflict-specific capital to facilitate renewed rebellion (opportunity structure).
The conflict that started in 2005 between the Free Life Party of Kurdistan (PJAK) and the Iranian government is a case in point. Kurdish opposition forces have repeatedly challenged the state in order to create an autonomous Kurdistan and put an end to the discriminatory and assimilatory policies of the regime. The conflict was last active in 1996, after which Mohammad Khatami’s presidency introduced at least some cultural and political freedoms for the Iranian Kurds, although they were still discriminated and politically excluded. With the election of Mahmoud Ahmadinejad as president in 2005, Kurdish hopes for reform were crushed, giving way to renewed conflict.[2]
The “bad neighborhood” pattern can be summarized as a situation of instability both at home and in the neighborhood. Ethnic groups that have warring ethnic kin across the border are likely to rebel themselves, but more so if the government at home is at the same time vulnerable because of political instability. This is the only one among the four patterns that included no incentive factor, but rather an extraordinary opportunity structure. This does not imply that mass grievances do not matter in this constellation, but they were not captured by my model.
An example here is the rebellion by the Tutsi-Banyamulenge in the Democratic Republic of the Congo (DRC). The Tutsi-led rebellion against the Hutu regime in neighboring Rwanda, the 1994 genocide of Tutsi and the defeat of the Hutu government forces all had a tremendous impact on the Tutsi in the DRC — at a time when the country was already at the brink of anarchy and president Mobutu lost crucial support from his Western allies by 1996.[3]
The “ousted rulers” pattern describes rebellions by groups who were recently excluded from central government power in a situation accompanied by political instability, leading both to grievances (loss of power and privileges) and opportunities (political instability, resources still available to the former power-holders).
A case in point here is the Sunni Arabs in Iraq in 2004, who lost the political advantages they enjoyed under Saddam Hussein’s regime when was ousted by the US-led invasion of Iraq. The subsequent Sunni Arab insurgency, while involving many opposition groups with diverse motives, is for many former regime members an attempt to regain lost power. To that end, they can draw on preexisting relationships and networks — and weapons.[4]
Finally, the “resource curse” pattern is a textbook example of grievances and opportunities coinciding at a certain point in time to facilitate violent uprising. When oil-rich but politically excluded groups can make use of the window of opportunity offered by political instability at the center, ethnic conflict is very likely. Here, political exclusion stands for groups’ grievances, while political instability is an opportunity factor. The presence of oil may fall under both categories. It can be a source of grievance if the population feels that the wealth from ‘their’ resources is siphoned away from the region while the population faces the negative externalities of the extraction process, such as environmental damage and displacement.[5] Oil could, however, also offer an opportunity to finance a rebellion, because many natural resources can be either looted or used for extortion.
The movement by the Bakongo and Cabindan Mayombe for the independence of the Angolan enclave of Cabinda is a typical case. This region accounts for more than half of Angola’s oil production, yet neither the political power nor the economic welfare of the two groups has been positively influenced by these riches.[6] At the same time, the presence of oil reserves may have influenced the strategic calculus of the rebels in Angola, fueling beliefs that ‘going it alone’ could be feasible and an independent Cabinda potentially prosperous.[7] When the instability caused by the country’s transition to multiparty democracy offered a window of opportunity in the early 1990s, the simmering conflict escalated.
Moving On
Within the scholarship on violent conflict, the isolated effects of all these risk factors are fairly well known. However, in this article I set out to empirically demonstrate the explanatory leverage we can gain by looking at the multiple — but not infinite — patterns they form. This, in turn, resulted in a model that predicts conflicts somewhat more successfully than a standard statistical model. Predictions are not only valuable to gauge the real-world usefulness of a conflict model – they also offer a way to compare empirical results across different research approaches. This facilitates communication across methodological boundaries and takes the heat out of unfruitful methodological disputes.
In this sense, a big part of this article is about building bridges between the camps, not just methodologically, but also theoretically. Theoretically, because the article makes a theoretical synthesis that aims to overcome rather than fan the debate — a debate that has always felt slightly inappropriate. The patterns that were identified suggest that it may be high time to abandon the ‘either-or framing’ of the greed-grievance debate in favor of a more inclusive approach.
You can read this article for free at the Journal of Peace Research.
[1] Charles Ragin (2000). Fuzzy-Set Social Science. Chicago: University of Chicago Press, p. 81.
[2] Gareth Stansfield, Robert Lowe and Hashem Ahmadzadeh (2007). The Kurdish Policy Imperative. Chatham House Briefing Paper.
[3] Gérard Prunier (2009). Africa’s World War: Congo, the Rwandan Genocide, and the Making of a Continental Catastrophe. Oxford: Oxford University Press.
[4] Michael Eisenstadt and Jeffrey White (2005). Assessing Iraq’s Sunni Arab Insurgency. Policy Focus #50. Washington, D.C.: The Washington Institute for Near East Policy.
[5] Mohammad Zulfan Tadjoeddin, Widjajanti I Suharyo and Satish Mishra (2001). Regional Disparity and Vertical Conflict in Indonesia. Journal of the Asia Pacific Economy 6(3): 283-304.
[6] Philippe le Billon (2001). Angola’s Political Economy of War: The Role of Oil and Diamonds, 1975–2000. African Affairs 100(398): 55-80.
[7]Macartan Humphreys (2005). Natural Resources, Conflict, and Conflict Resolution: Uncovering the Mechanisms. Journal of Conflict Resolution 49(4): 508-37.
Corinne Bara is a PhD candidate at the Center for Security Studies (CSS). Prior to entering the PhD program, she worked as a researcher in the Risk & Resilience Research Group at the CSS, where she specialized in research on risk analysis and disaster management with a focus on resilience and social vulnerability.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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