491 research outputs found
Location, Location, Location: An MCMC Approach to Modeling the Spatial Context of War and Peace
This article demonstrates how spatially dependent data with a categorical response variable can be addressed in a statistical model. We introduce the idea of an autologistic model where the response for one observation is dependent on the value of the response among adjacent observations. The autologistic model has likelihood function that is mathematically intractable, since the observations are conditionally dependent upon one another. We review alternative techniques for estimating this model, with special emphasis on recent advances using Markov chain Monte Carlo (MCMC) techniques. We evaluate a highly simplified autologistic model of conflict where the likelihood of war involvement for each nation is conditional on the war involvement of proximate states. We estimate this autologistic model for a single year (1988) via maximum pseudolikelihood and MCMC maximum likelihood methods. Our results indicate that the autologistic model fits the data much better than an unconditional model and that the MCMC estimates generally dominate the pseudolikelihood estimates. The autologistic model generates predicted probabilities greater than 0.5 and has relatively good predictive abilities in an out-of-sample forecast for the subsequent decade (1989 to 1998), correctly identifying not only ongoing conflicts, but also new ones.</jats:p
Words and Deeds: From Incompatibilities to Outcomes in Anti-Government Disputes
Dissidents can choose among different tactics to redress political grievances, yet violent and nonviolent mobilization tend to be studied in isolation. We examine why some countries see the emergence of organized dissident activity over governmental claims, and why in some cases these organizational claims result in civil wars or nonviolent campaigns, while others see no large-scale collective action. We develop a two-stage theoretical framework examining the organized articulation of political grievance and then large-scale violent and nonviolent collective action. We test implications of this framework using new data on governmental incompatibilities in a random sample of 101 states from 1960- 2012. We show that factors such as demography, economic development and civil society have differential effects on these different stages and outcomes of mobilization. We demonstrate that the common finding that anocracies are more prone to civil war primarily stems from such regimes being more prone to see maximalist political demands that could lead to violent mobilization, depending on other factors conducive to creating focused military capacity We find that non-democracy generally promotes nonviolent campaigns as anocracies and autocracies are both more likely to experience claims and more prone to nonviolent campaigns, conditional on claims
Clustering in Complex Directed Networks
Many empirical networks display an inherent tendency to cluster, i.e. to form
circles of connected nodes. This feature is typically measured by the
clustering coefficient (CC). The CC, originally introduced for binary,
undirected graphs, has been recently generalized to weighted, undirected
networks. Here we extend the CC to the case of (binary and weighted) directed
networks and we compute its expected value for random graphs. We distinguish
between CCs that count all directed triangles in the graph (independently of
the direction of their edges) and CCs that only consider particular types of
directed triangles (e.g., cycles). The main concepts are illustrated by
employing empirical data on world-trade flows
Patterns of dominant flows in the world trade web
The large-scale organization of the world economies is exhibiting
increasingly levels of local heterogeneity and global interdependency.
Understanding the relation between local and global features calls for
analytical tools able to uncover the global emerging organization of the
international trade network. Here we analyze the world network of bilateral
trade imbalances and characterize its overall flux organization, unraveling
local and global high-flux pathways that define the backbone of the trade
system. We develop a general procedure capable to progressively filter out in a
consistent and quantitative way the dominant trade channels. This procedure is
completely general and can be applied to any weighted network to detect the
underlying structure of transport flows. The trade fluxes properties of the
world trade web determines a ranking of trade partnerships that highlights
global interdependencies, providing information not accessible by simple local
analysis. The present work provides new quantitative tools for a dynamical
approach to the propagation of economic crises
The World-Trade Web: Topological Properties, Dynamics, and Evolution
This paper studies the statistical properties of the web of import-export
relationships among world countries using a weighted-network approach. We
analyze how the distributions of the most important network statistics
measuring connectivity, assortativity, clustering and centrality have
co-evolved over time. We show that all node-statistic distributions and their
correlation structure have remained surprisingly stable in the last 20 years --
and are likely to do so in the future. Conversely, the distribution of
(positive) link weights is slowly moving from a log-normal density towards a
power law. We also characterize the autoregressive properties of
network-statistics dynamics. We find that network-statistics growth rates are
well-proxied by fat-tailed densities like the Laplace or the asymmetric
exponential-power. Finally, we find that all our results are reasonably robust
to a few alternative, economically-meaningful, weighting schemes.Comment: 44 pages, 39 eps figure
The International Trade Network: weighted network analysis and modelling
Tools of the theory of critical phenomena, namely the scaling analysis and
universality, are argued to be applicable to large complex web-like network
structures. Using a detailed analysis of the real data of the International
Trade Network we argue that the scaled link weight distribution has an
approximate log-normal distribution which remains robust over a period of 53
years. Another universal feature is observed in the power-law growth of the
trade strength with gross domestic product, the exponent being similar for all
countries. Using the 'rich-club' coefficient measure of the weighted networks
it has been shown that the size of the rich-club controlling half of the
world's trade is actually shrinking. While the gravity law is known to describe
well the social interactions in the static networks of population migration,
international trade, etc, here for the first time we studied a non-conservative
dynamical model based on the gravity law which excellently reproduced many
empirical features of the ITN.Comment: 5 pages, 5 figure
Contagion or Confusion? Why Conflicts Cluster in Space
Civil wars cluster in space as well as time. In this study, we develop and evaluate empirically alternative explanations for this observed clustering. We consider whether the spatial pattern of intrastate conflict simply stems from a similar distribution of relevant country attributes or whether conflicts indeed constitute a threat to other proximate states. Our results strongly suggest that there is a genuine neighborhood effect of armed conflict, over and beyond what individual country characteristics can account for. We then examine whether the risk of contagion depends on the degree of exposure to proximate conflicts. Contrary to common expectations, this appears not to be the case. Rather, we find that conflict is more likely when there are ethnic ties to groups in a neighboring conflict and that contagion is primarily a feature of separatist conflicts. This suggests that transnational ethnic linkages constitute a central mechanism of conflict contagion. © 2008 International Studies Association
Introduction to Special Issue on “Disaggregating Civil War”
We introduce the contributions to this special issue on “Disaggregating Civil War.” We review the problems arising from excessive aggregation in studies of civil war, and outline how disaggregation promises to provide better insights into the causes and dynamics of civil wars, using the articles in this special issue as examples. We comment on the issue of the appropriate level of disaggregation, lessons learned from these articles, and issues for further research. </jats:p
Null Models of Economic Networks: The Case of the World Trade Web
In all empirical-network studies, the observed properties of economic
networks are informative only if compared with a well-defined null model that
can quantitatively predict the behavior of such properties in constrained
graphs. However, predictions of the available null-model methods can be derived
analytically only under assumptions (e.g., sparseness of the network) that are
unrealistic for most economic networks like the World Trade Web (WTW). In this
paper we study the evolution of the WTW using a recently-proposed family of
null network models. The method allows to analytically obtain the expected
value of any network statistic across the ensemble of networks that preserve on
average some local properties, and are otherwise fully random. We compare
expected and observed properties of the WTW in the period 1950-2000, when
either the expected number of trade partners or total country trade is kept
fixed and equal to observed quantities. We show that, in the binary WTW,
node-degree sequences are sufficient to explain higher-order network properties
such as disassortativity and clustering-degree correlation, especially in the
last part of the sample. Conversely, in the weighted WTW, the observed sequence
of total country imports and exports are not sufficient to predict higher-order
patterns of the WTW. We discuss some important implications of these findings
for international-trade models.Comment: 39 pages, 46 figures, 2 table
The International-Trade Network: Gravity Equations and Topological Properties
This paper begins to explore the determinants of the topological properties
of the international - trade network (ITN). We fit bilateral-trade flows using
a standard gravity equation to build a "residual" ITN where trade-link weights
are depurated from geographical distance, size, border effects, trade
agreements, and so on. We then compare the topological properties of the
original and residual ITNs. We find that the residual ITN displays, unlike the
original one, marked signatures of a complex system, and is characterized by a
very different topological architecture. Whereas the original ITN is
geographically clustered and organized around a few large-sized hubs, the
residual ITN displays many small-sized but trade-oriented countries that,
independently of their geographical position, either play the role of local
hubs or attract large and rich countries in relatively complex
trade-interaction patterns
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