Using updated Archigos Data, as well as structural and event data, we construct a split-population duration model of irregular leadership changes. These are leadership changes that occur outside of the normal, legal framework for leadership transitions. Our model was estimated in March 2014 and produced probability estimates of leadership changes in many countries in the world. We used a wisdom-of-the-crowds approach to combining estimates from various different models. Ukraine and Thailand are among those in which we had the highest predictions for irregular change of leaders.
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Beger et al. (2014) studied this question.
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