Replication Data for: [W]hat lies beneath: Using Latent Networks to Improve Spatial Predictions of Political Violence
Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)
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Title |
Replication Data for: [W]hat lies beneath: Using Latent Networks to Improve Spatial Predictions of Political Violence
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Identifier |
https://doi.org/10.7910/DVN/LP6JP2
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Creator |
Dorff, Cassy
Gallop, Max Minhas, Shahryar |
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Publisher |
Harvard Dataverse
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Description |
Spatial interdependencies commonly drive the spread of violence in civil conflict. To address such interdependence, scholars often use spatial lags to model the diffusion of violence, but this requires an explicit operationalization of the connectivity matrices that represent the spread of conflict. Unfortunately, in many cases, there are multiple competing processes that facilitate the spread of violence making it difficult to identify the true data-generating process. We show how a network driven methodology can allow us to account for the spread of violence, even in the cases where we cannot directly measure the factors that drive diffusion. To do so, we estimate a latent connectivity matrix that captures a variety of possible diffusion patterns. We use this procedure to study intrastate conflict in eight conflict-prone countries and show how our framework enables substantially better predictive performance than canonical spatial lag measures. We also investigate the circumstances under which canonical spatial lags suffice, and those under which a latent network approach is beneficial.
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Subject |
Social Sciences
conflict, spatial, latent space |
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Contributor |
Minhas, Shahryar
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