Michael Spagat

Common ecology quantifies human insurgency

Many collective human activities, including violence, have been shown to exhibit universal patterns. The size distributions of casualties both in whole wars from 1816 to 1980 and terrorist attacks have separately been shown to follow approximate power-law distributions. However, the possibility of universal patterns ranging across wars in the size distribution or timing of within-conflict events has barely been explored. Here we show that the sizes and timing of violent events within different insurgent conflicts exhibit remarkable similarities. We propose a unified model of human insurgency that reproduces these commonalities, and explains conflict-specific variations quantitatively in terms of underlying rules of engagement. Our model treats each insurgent population as an ecology of dynamically evolving, self-organized groups following common decision-making processes. Our model is consistent with several recent hypotheses about modern insurgency, is robust to many generalizations, and establishes a quantitative connection between human insurgency, global terrorism and ecology. Its similarity to financial market models provides a surprising link between violent and non-violent forms of human behaviour.

Learning, experimentation, and monetary policy☆

We present a model of monetary policy where the policymaker faces uncertainty about wich he is learning in a Bayesian fashion. A fixed money supply levels. A fixed money supply rule is not optimal in this context since the learning leads to constant adjustments in money supply levels. We present cases in which it is optimal to bear some cost in terms of current output performance in order to gain information that can be used in the formulation of future monetary policy : experimentation therefore pays. We also show that even passive learning without experimentation still leads to an activist monetary policy, i.e. one that is constantly changing in response to new information.

Casualties in civilians and coalition soldiers from suicide bombings in Iraq, 2003–10: a descriptive study

BACKGROUND Suicide bombs in Iraq are a major public health problem. We aimed to describe documented casualties from suicide bombs in Iraq during 2003-10 in Iraqi civilians and coalition soldiers. METHODS In this descriptive study, we analysed and compared suicide bomb casualties in Iraq that were documented in two datasets covering March 20, 2003, to Dec 31, 2010--one reporting coalition-soldier deaths from suicide bombs, the other reporting deaths and injuries of Iraqi civilians from armed violence. We analysed deaths and injuries over time, by bomb subtype and victim demographics. FINDINGS In 2003-10, 1003 documented suicide bomb events caused 19% (42,928 of 225,789) of all Iraqi civilian casualties in our dataset, 26% (30,644 of 117,165) of injured civilians, and 11% (12,284 of 108,624) of civilian deaths. The injured-to-killed ratio for civilians was 2·5 people injured to one person killed from suicide bombs. Suicide bombers on foot caused 43% (5314 of 12,284) of documented suicide bomb deaths. Suicide bombers who used cars caused 40% (12,224 of 30,644) of civilian injuries. Of 3963 demographically identifiable suicide bomb fatalities, 2981 (75%) were men, 428 (11%) were women, and 554 (14%) were children. Children made up a higher proportion of demographically identifiable deaths from suicide bombings than from general armed violence (9%, 3669 of 40,276 deaths; p<0·0001). The injured-to-killed ratio for all suicide bombings was slightly higher for women than it was for men (p=0·02), but the ratio for children was lower than it was for both women (p<0·0001) and men (p=0·0002). 200 coalition soldiers were killed in 79 suicide bomb events during 2003-10. More Iraqi civilians per lethal event were killed than were coalition soldiers (12 vs 3; p=0·004). INTERPRETATION Suicide bombers in Iraq kill significantly more Iraqi civilians than coalition soldiers. Among civilians, children are more likely to die than adults when injured by suicide bombs. FUNDING None.

Estimating War Deaths An Arena of Contestation

In a much-cited recent article, Obermeyer, Murray, and Gakidou (2008a) examine estimates of wartime fatalities from injuries for thirteen countries. Their analysis poses a major challenge to the battle-death estimating methodology widely used by conflict researchers, engages with the controversy over whether war deaths have been increasing or decreasing in recent decades, and takes the debate over different approaches to battle-death estimation to a new level. In making their assessments, the authors compare war death reports extracted from World Health Organization (WHO) sibling survey data with the battle-death estimates for the same countries from the International Peace Research Institute, Oslo (PRIO). The analysis that leads to these conclusions is not compelling, however. Thus, while the authors argue that the PRIO estimates are too low by a factor of three, their comparison fails to compare like with like. Their assertion that there is “no evidence” to support the PRIO finding that war deaths have recently declined also fails. They ignore war-trend data for the periods after 1994 and before 1955, base their time trends on extrapolations from a biased convenience sample of only thirteen countries, and rely on an estimated constant that is statistically insignificant.

Violent Deaths of Iraqi Civilians, 2003–2008: Analysis by Perpetrator, Weapon, Time, and Location

Madelyn Hsiao-Rei Hicks and colleagues provide a detailed analysis of Iraqi civilian violent deaths during 2003-2008 of the Iraq war and show that of 92,614 deaths, unknown perpetrators caused 74% of deaths, Coalition forces 12%, and Anti-Coalition forces 11%.

The Weapons That Kill Civilians — Deaths of Children and Noncombatants in Iraq, 2003–2008

Dr. Madelyn Hicks and colleagues used the Iraq Body Count database to determine the nature and effects of various weapons on civilians in Iraq. They are now convinced that documenting the particular causes of violent civilian deaths during armed conflict is essential, both to prevent civilian harm and to monitor compliance with international humanitarian law.

Bias in epidemiological studies of conflict mortality

Cluster sampling has recently been used to estimate the mortality in various conflicts around the world. The Burnham et al. study on Iraq employs a new variant of this cluster sampling methodology. The stated methodology of Burnham et al. is to (1) select a random main street, (2) choose a random cross street to this main street, and (3) select a random household on the cross street to start the process. The authors show that this new variant of the cluster sampling methodology can introduce an unexpected, yet substantial, bias into the resulting estimates, as such streets are a natural habitat for patrols, convoys, police stations, road-blocks, cafes, and street-markets. This bias comes about because the residents of households on cross-streets to the main streets are more likely to be exposed to violence than those living further away. Here, the authors develop a mathematical model to gauge the size of the bias and use the existing evidence to propose values for the parameters that underlie the model. The research suggests that the Burnham et al. study of conflict mortality in Iraq may represent a substantial overestimate of mortality. Indeed, the recently published Iraq Family Health Survey covered virtually the same time period as the Burnham et al. study, used census-based sampling techniques, and produced a central estimate for violent deaths that was one fourth of the Burnham et al. estimate. The authors provide a sensitivity analysis to help readers to tune their own judgements on the extent of this bias by varying the parameter values. Future progress on this subject would benefit from the release of high-resolution data by the authors of the Burnham et al. study.

Special Data Feature; The Severity of the Colombian Conflict: Cross-Country Datasets Versus New Micro-Data

This article compares the treatment of Colombia in large cross-country conflict datasets with the information of a unique dataset on the Colombian conflict (CERAC). The big datasets display a strong tendency to record fewer killings than does CERAC. Moreover, when the big datasets provide annual time series on the conflict, these figures look either erratic or flat compared to CERAC’s and often move in different directions. The article also examines the criteria of the Uppsala Conflict Data Program (UCDP) for dataset inclusion and finds them considerably more restrictive than CERAC’s. The primary differences are that UCDP generally excludes attacks purely on civilians and any activity of illegal right-wing paramilitary groups. It is argued here that these omissions impoverish our perception of many civil wars. A calculated modified series based on UCDP methodology and CERAC raw information closes 56% of the gap between the two approaches. The remainder appears to derive mainly from a number of small events in CERAC but not UCDP, reflecting the limits of English-language press coverage of Colombia, upon which UCDP data is based. The gap with other big datasets is also closed. The dynamics of the lower-bound UCDP curve clearly resemble the modified CERAC curve, so UCDP does reasonably well on its own terms. A brief Northern Ireland case study is consistent with our Colombia conclusions. The article concludes with a recommendation for conflict researchers to prioritize the construction of more micro-datasets that will facilitate detailed studies of conflict intensity and its dynamics.

Growth under uncertainty with experimentation

Abstract We introduce Bayesian learning into a stochastic growth model and study the effect of experimentation on the optimal level of the investment decision and on the amount of information gathering. When more investment produces more information, experimentation can push towards a lower level of investment, thus reducing information acquisition. Symmetrically, when more investment reduces information, experimentation can increase investment and again decrease information gathering. These results run contrary to intuitions generated by the standard literature on experimentation.

Human Capital, Growth and Inequality in Transition Economies

Transition economies have an initial condition of high human capital relative to living standards. I explore the possible implications of this key fact by surveying and adapting literature on growth and inequality. I focus especially on the long run and policy options.