power-laws in terms of network degree distribution,

http://www.drewconway.com/zia/?p=212

 

Wars Have Power-Law Distribution Too

Chris Albon over at War & Health pointed me to a very interesting article on a recent scientific study that found the distribution casualties per attack in given years across several different wars followed a power-law distribution. The authors use this observation to create a simple mathematical formula, which Chris has conveniently posted, to predict the number of attacks causing some number of casualties in the next year. The trick in the formula is raising the product of (average number of attacks per year)(number of casualties per attack) to a constant power-law exponent, in this case -2.5.
I write a lot about power-laws in terms of network degree distribution, and I find this observation fascinating, but like any good research the ultimate outcome is more questions. What is the relation between the organizational structures of these conflicts and the distribution of attacks (very hard to answer, given the data requirements)? To what extent can this model be fit to high-intensity conflicts (seems to me they are only fitting it to low-intensity)? Can the model be made richer by adding extremely granular conflict data, e.g. the MNFI SIGACTs database (similar to what Palintir claims to have conducted)?
One worry about such a model, though, is how policy makers can interpret it. The Iraq conflict has been the most statistically analyzed war in our history due to the availability of data; making it easy for policy makers to “benchmark” success or failure. With this model, policy makers could use a predicted number of casualties as a means to assess progress. For example, falling 10 casualties short of the predicted number could be interpreted as the mark of a successful policy; however, this is very problematic and ignores the political reality of low-intensity conflicts like Iraq and Afghanistan.


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