Bayesian hidden Markov models for latent variable labeling assignments in conflict research: application to the role ceasefires play in conflict dynamics

TL;DR

This paper introduces a Bayesian autoregressive hidden Markov model to semi-supervisedly label latent conflict regimes, enabling direct analysis of ceasefires' impact on conflict dynamics using new comprehensive ceasefire data.

Contribution

It presents a novel Bayesian HMM framework for semi-supervised latent regime labeling in conflict research, incorporating uncertainty quantification and applying it to the new ETH-PRIO ceasefire dataset.

Findings

The model effectively labels latent conflict regimes with uncertainty estimates.

Analysis reveals the impact of ceasefires on conflict intensity and duration.

First systematic analysis of the ETH-PRIO ceasefire data in a cross-country context.

Abstract

A crucial challenge for solving problems in conflict research is in leveraging the semi-supervised nature of the data that arise. Observed response data such as counts of battle deaths over time indicate latent processes of interest such as intensity and duration of conflicts, but defining and labeling instances of these unobserved processes requires nuance and imprecision. The availability of such labels, however, would make it possible to study the effect of intervention-related predictors - such as ceasefires - directly on conflict dynamics (e.g., latent intensity) rather than through an intermediate proxy like observed counts of battle deaths. Motivated by this problem and the new availability of the ETH-PRIO Civil Conflict Ceasefires data set, we propose a Bayesian autoregressive (AR) hidden Markov model (HMM) framework as a sufficiently flexible machine learning approach for semi-supervised regime labeling with uncertainty quantification. We motivate our approach by illustrating the way it can be used to study the role that ceasefires play in shaping conflict dynamics. This ceasefires data set is the first systematic and globally comprehensive data on ceasefires, and our work is the first to analyze this new data and to explore the effect of ceasefires on conflict dynamics in a comprehensive and cross-country manner.