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Networks in Conflict: Theory and Evidence from the Great War of Africa

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  • König, Michael
  • Rohner, Dominic
  • Thoenig, Mathias
  • Zilibotti, Fabrizio

Abstract

We study from both a theoretical and an empirical perspective how a network of military alliances and enmities affects the intensity of a conflict. The model combines elements from network theory and from the politico-economic theory of conflict. We postulate a Tullock contest success function augmented by an externality: each group’s strength is increased by the fighting effort of its allies, and weakened by the fighting effort of its rivals. We obtain a closed form characterization of the Nash equilibrium of the fighting game, and of how the network structure affects individual and total fighting efforts. We then perform an empirical analysis using data on the Second Congo War, a conflict that involves many groups in a complex network of informal alliances and rivalries. We estimate the fighting externalities, and use these to infer the extent to which the conflict intensity can be reduced through (i) removing individual groups involved in the conflict; (ii) pacification policies aimed at alleviating animosity among groups.

Suggested Citation

  • König, Michael & Rohner, Dominic & Thoenig, Mathias & Zilibotti, Fabrizio, 2015. "Networks in Conflict: Theory and Evidence from the Great War of Africa," CEPR Discussion Papers 10348, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:10348
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    References listed on IDEAS

    as
    1. Coralio Ballester & Marc Vorsatz, 2014. "Random Walk-Based Segregation Measures," The Review of Economics and Statistics, MIT Press, vol. 96(3), pages 383-401, July.
    2. Mariaflavia Harari & Eliana La Ferrara, 2012. "Conflict, Climate and Cells: A disaggregated analysis," Working Papers 461, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    3. Nicolas Berman & Mathieu Couttenier & Dominic Rohner & Mathias Thoenig, 2017. "This Mine Is Mine! How Minerals Fuel Conflicts in Africa," American Economic Review, American Economic Association, vol. 107(6), pages 1564-1610, June.
    4. Nicolas Berman & Mathieu Couttenier & Dominic Rohner & Mathias Thoenig, 2017. "This Mine Is Mine! How Minerals Fuel Conflicts in Africa," American Economic Review, American Economic Association, vol. 107(6), pages 1564-1610, June.
    5. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    6. Jack Hirshleifer, 1989. "Conflict and rent-seeking success functions: Ratio vs. difference models of relative success," Public Choice, Springer, vol. 63(2), pages 101-112, November.
    7. Oliver Vanden Eynde, 2018. "Targets of Violence: Evidence from India's Naxalite Conflict," Economic Journal, Royal Economic Society, vol. 128(609), pages 887-916, March.
    8. Kenan Huremovic, 2014. "Rent Seeking and Power Hierarchies: A Noncooperative Model of Network Formation with Antagonistic Links," Working Papers 2014.45, Fondazione Eni Enrico Mattei.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Africa; alliances; civil conflict; Congo War; contest success function; enmities; network; rainfall;

    JEL classification:

    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • D74 - Microeconomics - - Analysis of Collective Decision-Making - - - Conflict; Conflict Resolution; Alliances; Revolutions
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • F51 - International Economics - - International Relations, National Security, and International Political Economy - - - International Conflicts; Negotiations; Sanctions

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