In the period 1946-2001, there were 225 armed conflicts and 34 of them were active in all of or part of 2001. Armed conflict remains a serious problem in the post-Cold War period. For three decades, the Correlates of War project has served as the main supplier of reliable data used in longitudinal studies of external and internal armed conflict. The COW datasets on war use the relatively high threshold of 1,000 battle-deaths. The Uppsala dataset on armed conflict has a lower threshold, 25 annual battle-deaths, but has so far been available for only the post-Cold War period. This dataset has now been backdated to the end of World War II. This article presents a report on armed conflict based on this backdate as well as another annual update. It presents the procedures for the backdating, as well as trends over time and breakdowns for the type of conflict. It assesses the criteria for measuring armed conflict and discusses some directions for future data collection in this area.

Contributions to the quantitative civil war literature increasingly rely on geo-referenced data and disaggregated research designs. While this is a welcome trend, it necessitates geographic information systems (GIS) skills and imposes new challenges for data collection and analysis. So far, solutions to these challenges differ between studies, obstructing direct comparison of findings and hampering replication and extension of earlier work. This article presents a standardized structure for storing, manipulating, and analyzing high-resolution spatial data. PRIO-GRID is a vector grid network with a resolution of 0.5 x 0.5 decimal degrees, covering all terrestrial areas of the world. Gridded data comprise inherently apolitical entities; the grid cells are fixed in time and space, they are insensitive to political boundaries and developments, and they are completely exogenous to likely features of interest, such as civil war outbreak, ethnic settlement patterns, extreme weather events, or the spatial distribution of wealth. Moreover, unlike other disaggregated approaches, gridded data may be scaled up or down in a consistent manner by varying the resolution of the grid. The released dataset comes with cell-specific information on a large selection of political, economic, demographic, environmental, and conflict variables for all years, 1946-2008. A simple descriptive data assessment of population density and economic activity is offered to demonstrate how PRIO-GRID may be applied in quantitative social science research.

This article examines how political institutional structures affect political instability. It classifies polities as autocracies or democracies based on three institutional dimensions: election of the executive, constraints on executive decision-making authority, and extent of political participation. It hypothesizes that strongly autocratic and democratic regimes will exhibit the greatest stability resulting from self-enforcing equilibria, whereby the maintenance of a polity's institutional structure is in the interest of political elites, whether through autocratic or democratic control. Institutionally inconsistent regimes (those exhibiting a mix of institutional characteristics of both democracy and autocracy) lack these self-enforcing characteristics and are expected to be shorter-lived. Using a log-logistic duration model, polity survival time ratios are estimated. Institutionally consistent polities are significantly more stable than institutionally inconsistent polities. The least stable political systems are dictatorships with high levels of political participation. The most unstable configuration for polities with an elected executive is one where the executive is highly constrained, but the electorate is very small. provided valuable comments and suggestions. A replication dataset and Stata do-files, as well as an online appendix containing the results of several alternative models, may be downloaded from

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Hegre, Håvard et al. (2012) Predicting Armed Conflict, 2010–2050. International Studies Quarterly, doi: 10.1111/isqu.12007 
© 2012 International Studies Association The article predicts changes in global and regional incidences of armed conflict for the 2010–2050 period. The predictions are based on a dynamic multinomial logit model estimation on a 1970–2009 cross‐sectional data set of changes between no armed conflict, minor conflict, and major conflict. Core exogenous predictors are population size, infant mortality rates, demographic composition, education levels, oil dependence, ethnic cleavages, and neighborhood characteristics. Predictions are obtained through simulating the behavior of the conflict variable implied by the estimates from this model. We use projections for the 2011–2050 period for the predictors from the UN World Population Prospects and the International Institute for Applied Systems Analysis. We treat conflicts, recent conflict history, and neighboring conflicts as endogenous variables. Out‐of‐sample validation of predictions for 2007–2009 (based on estimates for the 1970–2000 period) indicates that the model predicts well, with an area under the receiver operator curve of 0.937. Using a p > .30 threshold for positive prediction, the true positive rate 7–9 years into the future is 0.79 and the False Positive Rate 0.085. We predict a continued decline in the proportion of the world's countries that have internal armed conflict, from about 15% in 2009 to 7% in 2050. The decline is particularly strong in the Western Asia and North Africa region and less clear in Africa south of Sahara. The remaining conflict countries will increasingly be concentrated in East, Central, and Southern Africa and in East and South Asia.

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The concept of peace has been under discussion in peace research from its start over 50 years ago. This article reviews the debate on broader and narrower conceptions of peace and investigates empirical patterns in the first 49 volumes of Journal of Peace Research, with some comparisons with Journal of Conflict Resolution. Negative peace, in the sense of reducing war, was the main focus in peace research from the inception. But positive peace, in the sense of cooperation or integration, has also always been on the peace research agenda, as reflected in the contents of both journals. Over time, a larger share of the articles in JPR has 'violence' or related terms in the title, while the incidence of the word 'peace' is fairly stable. Furthermore, articles on peace generally have fewer citations than those with violence-related terms. A broad concept of peace, as encouraged by the definition of positive peace as the reversal of structural violence, was popular in peace research for a decade or so, but has largely evaporated. To some extent, peace research has returned to its original agenda, although the main attention has shifted from interstate war to civil war and to some extent to one-sided and non-state violence. Articles dealing with patterns of cooperation, the traditional meaning of positive peace, now tend to address the liberal agenda and ask how they can foster a reduced probability of violence. Despite the 'gender gap', the increasing share of female authors in the journal appears to have had little influence on these developments although it may well have had other effects.

Many studies report lower academic productivity among women. But are women less likely to get their research published in the first place? The evidence for potential gender bias in publication and impact is mixed. This article examines the gender dimension of scientific publication in international relations (IR) based on submission data for Journal of Peace Research for the period 1983–2008. It examines the gender gap in submissions and explores whether the perceived merit of a research paper is affected by the gender of the authors and reviewers. It also investigates whether the gender of the first author influences citation counts. The data show a clear but declining gender gap. They do not indicate any significant gender bias in publication success or citations.