B1293
Title: A Bayesian framework for studying climate anomalies and social conflicts
Authors: Snigdhansu Chatterjee - University Of Minnesota (United States) [presenting]
Abstract: Climate change stands to have a profound impact on human society and, in particular, on political and other conflicts. However, the existing literature on understanding the relationship between climate change and societal conflicts has often been criticized for using data that suffer from sampling and other biases, often resulting from being too narrowly focused on a small region of space or a small set of events. These studies have likewise been critiqued for not using suitable statistical tools that address spatiotemporal dependencies, obtain probabilistic uncertainty quantification, and lead to consistent statistical inferences. A Bayesian framework is proposed to address these challenges, with results exhibiting considerably nuanced relationships between temperature deviations and social conflicts that have yet to be noticed in previous studies. Methodologically, the proposed Bayesian framework can help social scientists explore similar domains involving large-scale spatial and temporal dependencies.
