The second Annual Bank Conference on Africa happened in Berkeley, CA, earlier this week, and the World Bank’s Development Impact blog has an outstanding summary of the 50-odd papers presented there. If you have to pick between reading this post and that one, go there.
One paper on that roster that caught my eye revisits the choice of statistical models for the study of civil wars. As authors John Paul Dunne and Nan Tian describe, the default choice is logistic regression, although probit gets a little playing time, too. They argue, however, that a zero-inflated Poisson (ZIP) model matches the data-generating process better than either of these traditional picks, and they show that this choice affects what we learn about the causes of civil conflict.
Having worked on statistical models of civil conflict for nearly 20 years, I have some opinions on that model-choice issue, but those aren’t what I want to discuss right now…
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