Uncertain Events: A Dynamic Latent Variable Model of Human Rights Respect and Government Killing with Binary, Ordered, and Count Outcomes
39 Pages Posted: 4 Mar 2014 Last revised: 16 Feb 2015
Date Written: July 28, 2013
Abstract
Counting repressive events is difficult because state leaders have an incentive to conceal the actions of their subordinates and destroy evidence of abuse. In this paper, I describe an existing latent variable model and then extend it to account for the uncertainty inherent in counting this type of difficult to observe event. To validate the model, I focus on one dataset, which defines one-sided government killing as government caused deaths of non-combatants. The model generates a more precise estimate of latent levels of repression for each country-year using several repression variables included in the model (1949-2010) and new estimates of the distribution of the number of individuals killed for each country-year in the original one-sided government killing dataset (1989-2010). These new event-based count estimates will be useful for researchers interested in this type of data but skeptical of the comparability of such events across countries and over time.
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