Social Identification in Civil War

  • Working Paper
  • 2021
  • Ravi Bhavnani, Karsten Donnay, Agnese Zucca

What determines who people side with and fight against in civil wars? Existing explanations conceive of identity and utility considerations as competing logics. We propose a shift from the strict dichotomy that has dominated theories of alliance formation, by advancing a model in which decisions can be driven by identity-based considerations, rational considerations, or some mix-of the two. The evidence-driven model is calibrated using original micro-level conflict data, and validated with case studies of two regions in Bosnia-Herzegovina.

Evidence-Driven Computational Modeling

An evidence-driven computational modeling (EDM) framework rests on three methodological pillars: agent-based computational modeling (ABM), empirical contextualization using geographical information systems (GIS), and empirical validation. The approach is especially useful in issue areas where there is an abundance of theoretical knowledge, outcomes are driven by complex interactions between numerous factors, and it is possible to leverage empirical data to seed or validate the model. Ideally, EDM provide evidence-driven results that decision-makers can use to evaluate alternative policy options in a systematic and transparent manner.

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The Morphology of Urban Conflict

  • Published Report
  • 2019
  • Ravi Bhavnani
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During the cold war, civil conflict had a rural bent, which research mirrored [1]. Urban environments were traditionally viewed as undermining identifications that provide an impetus for fighting [2], too well protected as the home bases of elites and even prohibitive to rebel operations [3]. As the world population grows and increasingly clusters in urban spaces [4], we argue that conflict will be redirected — whether purposefully or unintentionally — to cities. Results from several recent studies provide substantial support for a nascent urban propensity towards conflict — an emerging urban shift.

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