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Measure for measure: how well do we measure micro-level conflict intensity?

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  • Verpoorten, Marijke

Abstract

Rich measures of micro-level violent conflict intensity are key for successfully providing insight into the legacy of civil war. Yet, the debate on how exactly conflict intensity should be measured has just started. This paper aims to fuel this awakening debate. It is demonstrated how existing and widely available data - population census data - can provide the basis for a useful measure of micro-level conflict intensity: a fine Wartime Excess Mortality Index (WEMI). It is argued that the proposed measure is particularly well suited for studying the legacy of civil wars that are characterized by a large death toll and by different forms of violence. The measure is illustrated for the case of Rwanda and it is shown that, in a straightforward empirical application of the impact of armed conflict on schooling, the estimated impact varies widely across WEMI and a large set of alternative conflict intensity measures for Rwanda. While the conflict intensity measure proposed in this paper requires further study and one probably needs a combination of various methodologies, this finding suggests the need for a careful understanding of what underlies the different measures and methodologies in use.

Suggested Citation

  • Verpoorten, Marijke, 2011. "Measure for measure: how well do we measure micro-level conflict intensity?," IOB Working Papers 2011.08, Universiteit Antwerpen, Institute of Development Policy (IOB).
    • Handle: RePEc:iob:wpaper:2011008
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    References listed on IDEAS

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    1. Kevin E. Davis (ed.), 2010. "Institutions and Economic Performance," Books, Edward Elgar Publishing, number 3467, December.
    2. Shemyakina, Olga, 2011. "The effect of armed conflict on accumulation of schooling: Results from Tajikistan," Journal of Development Economics, Elsevier, vol. 95(2), pages 186-200, July.
    3. Tom Bundervoet & Philip Verwimp & Richard Akresh, 2009. "Health and Civil War in Rural Burundi," Journal of Human Resources, University of Wisconsin Press, vol. 44(2).
    4. Marijke verpoorten, 2010. "Detecting Hidden Violence: The Spatial Distribution of Excess Mortality in Rwanda," LICOS Discussion Papers 25410, LICOS - Centre for Institutions and Economic Performance, KU Leuven.
    5. Patricia Justino & Philip Verwimp, 2013. "Poverty Dynamics, Violent Conflict, and Convergence in R wanda," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 59(1), pages 66-90, March.
    6. Li, Baibing & Martin, Elaine B. & Morris, A. Julian, 2002. "On principal component analysis in L1," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 471-474, September.
    7. Philip Verwimp & Jan Van Bavel, 2004. "Child Survival and the Fertility of Refugees in Rwanda after the Genocide," PRUS Working Papers 26, Poverty Research Unit at Sussex, University of Sussex.
    8. de Walque, Damien, 2004. "The long-term legacy of the Khmer Rouge period in Cambodia," Policy Research Working Paper Series 3446, The World Bank.
    9. Miguel, Edward & Roland, Gérard, 2011. "The long-run impact of bombing Vietnam," Journal of Development Economics, Elsevier, vol. 96(1), pages 1-15, September.
    10. Deininger,Klaus W., 2003. "Causes and consequences of civil strife - micro-level evidence from Uganda," Policy Research Working Paper Series 3045, The World Bank.
    11. Gianmarco León, 2012. "Civil Conflict and Human Capital Accumulation: The Long-term Effects of Political Violence in Perú," Journal of Human Resources, University of Wisconsin Press, vol. 47(4), pages 991-1022.
    12. repec:cai:poeine:pope_504_0331 is not listed on IDEAS
    13. María A. González & Rigoberto A. Lopez, 2007. "Political Violence and Farm Household Efficiency in Colombia," Economic Development and Cultural Change, University of Chicago Press, vol. 55, pages 367-392.
    14. Brück, Tilman & Justino, Patricia & Verwimp, Philip & Avdeenko, Alexandra, 2010. "Identifying Conflict and Violence in Micro-Level Surveys," IZA Discussion Papers 5067, Institute for the Study of Labor (IZA).
    15. Tom Bundervoet, 2006. "Livestock, Activity Choices and Conflict: Evidence from Burundi," HiCN Working Papers 24, Households in Conflict Network.
    16. Chamarbagwala, Rubiana & Morán, Hilcías E., 2011. "The human capital consequences of civil war: Evidence from Guatemala," Journal of Development Economics, Elsevier, vol. 94(1), pages 41-61, January.
    17. Marijke Verpoorten, 2010. "The intensity of the Rwandan genocide: Fine measures from the gacaca records," LICOS Discussion Papers 25610, LICOS - Centre for Institutions and Economic Performance, KU Leuven.
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    Cited by:

    1. Tilman Brück & Patricia Justino & Philip Verwimp & Andrew Tedesco & Alexandra Avdeenko, 2013. "Measuring Conflict Exposure in Micro-Level Surveys," HiCN Working Papers 153, Households in Conflict Network.
    2. Serneels , Pieter & Verpoorten , Marijke, 2012. "The impact of armed conflict on economic performance. Evidence from Rwanda," NEPS Working Papers 5/2012, Network of European Peace Scientists.

    More about this item

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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