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Estimating the intensity of conflict in Iraq

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  • Guy P. Nason
  • Daniel Bailey

Abstract

Summary. Since 2003 several Web sites have appeared that track the number of deaths of coalition personnel in the current Iraq conflict. The paper proposes the use of a recently developed multiscale variance stabilization method (the data‐driven Haar–Fisz transform) to obtain good estimates of the mean intensity of deaths and demonstrates its statistical advantages over both the running mean (which is currently used on some Web sites) and also the Box–Cox transformation. The paper analyses both the number of deaths due to all causes and also due to hostile actions between June 2003 and March 2006. In both cases it appears that the marginal variance of both time series is an increasing function of the marginal mean. Further, although our estimates exhibit peaks that are related to local increases in intensity of conflict there appears to be a clear underlying increase in intensity of conflict during the conflict but with a decline and levelling off since June 2005. The paper also proposes a tentative inverse relationship between deaths due to non‐hostile actions and deaths due to hostile actions.

Suggested Citation

  • Guy P. Nason & Daniel Bailey, 2008. "Estimating the intensity of conflict in Iraq," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(4), pages 899-914, October.
    • Handle: RePEc:bla:jorssa:v:171:y:2008:i:4:p:899-914
    DOI: 10.1111/j.1467-985X.2008.00540.x
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    References listed on IDEAS

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    1. Jung, Robert C. & Kukuk, Martin & Liesenfeld, Roman, 2006. "Time series of count data: modeling, estimation and diagnostics," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2350-2364, December.
    2. Fryzlewicz, Piotr & Delouille, V´eronique & Nason, Guy P., 2007. "GOES-8 X-ray sensor variance stabilization using the multiscale data-driven Haar-Fisz transform," LSE Research Online Documents on Economics 25221, London School of Economics and Political Science, LSE Library.
    3. Piotr Fryzlewicz & Véronique Delouille & Guy P. Nason, 2007. "GOES‐8 X‐ray sensor variance stabilization using the multiscale data‐driven Haar–Fisz transform," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 56(1), pages 99-116, January.
    4. Johnstone, Iain & Silverman, Bernard W., 2005. "EbayesThresh: R Programs for Empirical Bayes Thresholding," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 12(i08).
    5. Breusch, T S & Pagan, A R, 1979. "A Simple Test for Heteroscedasticity and Random Coefficient Variation," Econometrica, Econometric Society, vol. 47(5), pages 1287-1294, September.
    6. Stuart Barber & Guy P. Nason, 2004. "Real nonparametric regression using complex wavelets," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(4), pages 927-939, November.
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    Cited by:

    1. Saralees Nadarajah, 2015. "A statistical analysis of Iraq body counts," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(1), pages 21-37, January.

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