Return to search

The Economics of Genocide and War

Preparing for Genocide: Community Work in Rwanda How do political elites prepare the civilian population for participation in violent conflict? We empirically investigate this question using village-level data from the Rwandan Genocide in 1994. Every Saturday before 1994, Rwandan villagers had to meet to work on community infrastructure, a practice called Umuganda. This practice was highly politicized and, before the genocide, regularly used by the local political elites for spreading propaganda. To establish causality, we exploit cross-sectional variation in meeting intensity induced by exogenous weather fluctuations. We find that a one standard-deviation increase in the number of rainy Saturdays resulted in a 20 percent lower civilian participation rate in genocide violence.   Mobilizing the Masses for Genocide Do political elites use armed groups to foster civilian participation in violence or are civilian killers driven by unstoppable ancient hatred? If armed groups matter, are they allocated strategically to maximize civilian participation? How do they mobilize civilians? I empirically investigate these three questions using village-level data from the Rwandan Genocide. To establish causality, I exploit cross-sectional variation in armed groups' transport costs induced by exogenous weather fluctuations: the shortest distance of each village to the main road interacted with rainfall along the dirt tracks between the main road and the village. Guided by a simple model, I come up with the following answers to the three central questions: (1) one additional armed-group member resulted in 7.3 more civilian perpetrators, (2) armed-group leaders responded rationally to exogenous transport costs and dispatched their men strategically to maximize civilian participation and (3) for the majority of villages, armed-group members acted as role models and civilians followed orders, but in villages with high levels of cross-ethnic marriage, civilians had to be forced to join in. Finally, a back-of-the-envelope calculation suggests that a military intervention targeting the various armed groups could have stopped the Rwandan Genocide.   The Legacy of Political Mass Killings: Evidence from the Rwandan Genocide We study how political mass killings affect later economic performance, using data from the Rwandan Genocide. Our results show that households in villages that experienced higher levels of violence have higher living standards six years after the genocide. They enjoy higher levels of consumption, own more assets and agricultural output per capita is higher. These results are consistent with the Malthusian hypothesis that mass killings can raise living standards by reducing the population size and redistributing assets from the deceased to the survivors. However, we also find that the violence affected the age distribution in villages, raised fertility rates among female survivors and reduced cognitive skills of children.   Ethnic Income Inequality and Conflict in Africa This paper shows that income inequality between ethnic groups increases the likelihood of ethnic conflict in Africa. To establish causality, we exploit variation in rainfall over each ethnic group’s homeland. One standard-deviation increase in ethnic inequality increases the likelihood of ethnic conflict by about 66 percent. Our results have important policy implications to the extent that global climate change might affect different regions differently and thus increase inequality and conflict.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:su-116793
Date January 2015
CreatorsRogall, Thorsten
PublisherStockholms universitet, Institutet för internationell ekonomi, Stockholm
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeDoctoral thesis, monograph, info:eu-repo/semantics/doctoralThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess
RelationMonograph series / Institute for International Economic Studies, University of Stockholm, 0346-6892 ; 86

Page generated in 0.0017 seconds