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Insurgency and Small Wars: Estimation of Unobserved Coalition Structures

Author

Listed:
  • Francesco Trebbi

    (University of British Columbia)

  • Eric Weese

    (Economics Department Yale University)

Abstract
Insurgency and guerrilla warfare impose enormous socio-economic costs and often persist for decades. The opacity of such forms of con flict is often an obstacle to effective international humanitarian intervention and development programs. To shed light on the internal organization of otherwise unknown insurgent groups, this paper proposes two methodologies for the detection of unobserved coalitions of militant factions in con ict areas, and studies their main determinants. Our approach is parsimonious and based on daily geocoded incident-level data on insurgent attacks alone. We provide applications to the Afghan con ict during the 2004-2009 period and to Pakistan during the 2008-2011 period, identifying systematically different coalition structures. Further applications are discussed.

Suggested Citation

  • Francesco Trebbi & Eric Weese, 2016. "Insurgency and Small Wars: Estimation of Unobserved Coalition Structures," Working Papers 1053, Economic Growth Center, Yale University.
    • Handle: RePEc:egc:wpaper:1053
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    File URL: http://egcenter.economics.yale.edu/sites/default/files/files/CDP-cdp1001-cdp1100/cdp1053.pdf
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    References listed on IDEAS

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    Cited by:

    1. Vincent A. Floreani & Gladys López-Acevedo & Martín Rama, 2021. "Conflict and Poverty in Afghanistan’s Transition," Journal of Development Studies, Taylor & Francis Journals, vol. 57(10), pages 1776-1790, October.
    2. Aleberto Alesina & Guido Tabellini & Francesco Trebbi, 2017. "Is Europe an Optimal Political Area?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 48(1 (Spring), pages 169-234.
    3. Trebbi, Francesco & Weese, Eric & Wright, Austin L. & Shaver, Andrew, 2020. "Insurgent Learning," Journal of Political Institutions and Political Economy, now publishers, vol. 1(3), pages 417-448, August.
    4. Yiran Chen & Hanming Fang, 2017. "Inferring the Ideological Affliations of Political Committees via Financial Contributions Networks," PIER Working Paper Archive 17-022, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 10 Dec 2017.
    5. Morales, Juan S., 2021. "Legislating during war: Conflict and politics in Colombia," Journal of Public Economics, Elsevier, vol. 193(C).
    6. Adlai Newson & Francesco Trebbi, 2018. "Authoritarian elites," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 51(4), pages 1088-1117, November.
    7. Stoop, Nik & Verpoorten, Marijke & van der Windt, Peter, 2019. "Artisanal or industrial conflict minerals? Evidence from Eastern Congo," World Development, Elsevier, vol. 122(C), pages 660-674.
    8. Cagé, Julia & Dagorret, Anna & Grosjean, Pauline & JHA, SAUMITRA, 2020. "Heroes and Villains: The Effects of Combat Heroism on Autocratic Values and Nazi Collaboration in France," CEPR Discussion Papers 15613, C.E.P.R. Discussion Papers.
    9. Julia Cagé & Anna Dagorret & Pauline Grosjean & Saumitra Jha, 2023. "Heroes and Villains: The Effects of Heroism on Autocratic Values and Nazi Collaboration in France," American Economic Review, American Economic Association, vol. 113(7), pages 1888-1932, July.
    10. Martin Gassebner & Paul Schaudt & Melvin H. L. Wong, 2020. "Armed Groups in Conflict: Competition and Political Violence in Pakistan," CESifo Working Paper Series 8372, CESifo.
    11. Gassebner, Martin & Schaudt, Paul & Wong, Melvin H.L., 2023. "Armed groups: Competition and political violence," Journal of Development Economics, Elsevier, vol. 162(C).
    12. Gehring, Kai & Langlotz, Sarah & Kienberger, Stefan, 2018. "Stimulant or depressant? Resource-related income shocks and conflict," Working Papers 0652, University of Heidelberg, Department of Economics.

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    More about this item

    Keywords

    coalition formation; mixed integer programming; moment inequalities; municipal mergers; myopic deviations;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D71 - Microeconomics - - Analysis of Collective Decision-Making - - - Social Choice; Clubs; Committees; Associations
    • H77 - Public Economics - - State and Local Government; Intergovernmental Relations - - - Intergovernmental Relations; Federalism
    • R53 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Public Facility Location Analysis; Public Investment and Capital Stock

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