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Contribution Details

Type Working Paper
Scope Discipline-based scholarship
Title Strategic Mass Killings
Organization Unit
Authors
  • Joan Esteban
  • Massimo Morelli
  • Dominic Rohner
Language
  • English
Institution University of Zurich
Series Name Working paper series / Institute for Empirical Research in Economics
Number No. 486
ISSN 1424-0459
Date 2010
Abstract Text "Since World War II there have been about fifty episodes of large-scale mass killings of civilians and massive forced displacements. They were usually meticulously planned and independent of military goals. We provide a model where conflict onset, conflict intensity and the decision to commit mass killings are all endogenous, with two main goals: (1) to identify the key variables and situations that make mass killings more likely to occur; and (2) to distinguish conditions under which mass killings and military conflict intensity reinforce each other from situations where they are substitute modes of strategic violence.nWe predict that mass killings are most likely in societies with large natural resources, significant proportionality constraints for rent sharing, low productivity and low state capacity. Further, massacres are more likely in a civil than in an interstate war, as in the latter group sizes matter less for future rents.nIn non polarized societies there are asymmetric equilibria with only the larger group wanting to engage in massacres. In such settings the smaller group compensates for this by fighting harder in the first place. In this case we can talk of mass killings and fighting efforts to be substitutes. In contrast, in polarized societies either both or none of the groups can be ready to do mass killings in case of victory. Under the 'shadow of mass killings' groups fight harder. Hence, in this case massacres and fighting are complements.nWe also present novel empirical results on the role of natural resources in mass killings and on what kinds of ethnic groups are most likely to be victimized in massacres and forced resettlements, using group level panel data."
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