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Important gaps remain in the understanding of the economic consequences of civil war. Focusing on the conflict in Rwanda in the early 1990s, and using micro data, this article finds that households and localities that experienced more intense conflict are lagging behind in terms of consumption six years after the conflict, a finding that is robust to taking into account the endogeneity of violence. Significantly different returns to land and labor are observed between zones that experienced low- and high-intensity conflict which is consistent with the ongoing recovery. Distinguishing between civil war and genocide, the findings also provide evidence that these returns, and by implication the process of recovery, depend on the form of violence.
We show that armed conflict in Uganda affects social capital as measured by trust and associational membership. Relying on three rounds of nationally representative individuallevel data bracketing a large number of violent events, we find that self-reported generalized trust and associational membership decreased during the conflict in districts in which violent events took place. But we also find evidence for a rapid recovery of social capital in the aftermath of violence. Results from a variety of identification strategies, including differencein-difference and instrumental variable estimates, suggests that these relationships are causal.
The Dodd Frank Act was passed by the US Congress in July 2010 and included a provision—Section 1502—that aimed to break the link between conflict and minerals in the Eastern Democratic Republic of Congo. To date there is only one rigorous quantitative analysis that investigates the impact of Dodd-Frank on local conflict events. Looking at the short-term impact (2011–2012), it finds that the policy backfired. This study builds on a larger, more representative, dataset of mining sites and extends the time horizon by three years (2013–2015). The results indicate that the policy also backfired in the longer run, especially in areas home to gold mines. For territories with the average number of gold mines, the introduction of Dodd-Frank increased the incidence of battles with 44%; looting with 51% and violence against civilians with 28%, compared to pre-Dodd Frank averages. Delving deeper into the impact of the conflict minerals legislation is important, as President Trump suspended the legislation in February 2017 for a two-year period, ordering his administration to replace it with another policy.
Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. www.econstor.eu In contrast, a number of sub-national analyses have provided some evidence for local conditional Malthusian catastrophes, although "catastrophe" is a big word since these studies have largely focused on low-intensity violence. This article adds to the small body of sub-national studies, but focuses on a high-intensity con ‡ict, the Rwandan genocide. In particular, it provides a meso-level analysis of the relation between population pressure and the intensity of violence measured by the death toll among the Tutsi across 1,294 small administrative units. The results indicate that the death toll was signi…cantly higher in localities with both high population density and little opportunity for young men to acquire land. On An earlier version of this paper was presented at a LICOS/CRED seminar in Leuven and the CSAE conference in Oxford. I received helpful comments from Giacomo De Luca, Nils Petter Gleditsch, Romain Houssa, Pieter Serneels and Henrik Urdal. I am indebted to Bert Ingelaere for bringing the Gacaca data to my attention. I owe thanks to the Rwandan National Service of Gacaca Jurisdiction and the Rwandan National Census Service for making available the data used in this study. All errors and opinions expressed remain my own.
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