Hot under the collar: A latent measure of interstate hostility
| Author | Zhanna Terechshenko |
| Date | 01 November 2020 |
| DOI | 10.1177/0022343320962546 |
| Published date | 01 November 2020 |
| Subject Matter | Regular Article |
Hot under the collar: A latent measure
of interstate hostility
Zhanna Terechshenko
Center for Social Media and Politics (CSMaP), New York University
Abstract
The majority of studies on international conflict escalation use a variety of measures of hostility including the use of
force, reciprocity, and the number of fatalities. The use of different measures, however, leads to different empirical
results and creates difficulties when testing existing theories of interstate conflict. Furthermore, hostility measures
currently used in the conflict literature are ill suited to the task of identifying consistent predictors of international
conflict escalation. This article presents a new dyadic latent measure of interstate hostility, created using a Bayesian
item-response theory model and conflict data from the Militarized Interstate Dispute (MID) and Phoenix political
event datasets. This model (1) provides a more granular, conceptually precise, and validated measure of hostility,
which incorporates the uncertainty inherent in the latent variable; and (2) solves the problem of temporal variation in
event data using a varying-intercept structure and human-coded data as a benchmark against which biases in
machine-coded data are corrected. In addition, this measurement model allows for the systematic evaluation of how
existing measures relate to the construct of hostility. The presented model will therefore enhance the ability of
researchers to understand factors affecting conflict dynamics, including escalation and de-escalation processes.
Keywords
international conflict escalation, interstate hostility, measurement, latent variable model
Introduction
Despite the existence of a relatively large body of theore-
tical and empirical research on conflict escalation, there is
still no consensus among international relations scholars
on why some interstate disputes lead to war while others
do not. Part of the explanation for this issue is that the
measures currently used in the quantitative interstate con-
flict literature are ill suited to the task of identifying con-
sistent predictors of conflict escalation. In this article, I
provide a theoretically motivatedmeasurement model that
enhances researchers’ ability to explain conflict processes.
In particular, I define interstate conflict escalation as an
increase in the level of hostility between countries
involved in a militarized conflict. This approach requires
a granular and validated measure of hostility – a variable
we cannot observe directly, but manifestations of
which we can. In this article, I create a latent measure
of interstate hostility by constructing a Bayesian ordinal
item-response theory model using conflict events data,
including the Dyadic Militarized Interstate Disputes
(MID) (Maoz et al., 2019; Palmer et al., 2015) and Phoe-
nix political event datasets (Althaus et al., 2017).
This project makes several contributions to the liter-
ature. First, it introduces a more precise and granular
measure of hostility as the model combines the accuracy
of the expert-coded MIDs and the granularity of the
Phoenix event datasets. By capturing the underlying ten-
sion in the relationship between states, this novel mea-
sure can help to answer theoretical questions related to
conflict dynamic processes including both escalation and
de-escalation of interstate conflcts. In addition, the
model employed in this article allows for the systematic
evaluation of howexisting measures relate to the construct
of hostility. By integrating some of these measures, the
model enables one to make inferences about their quality.
In addition, my new measure of hostility incorporates
Corresponding author:
zt10@nyu.edu
Journal of Peace Research
2020, Vol. 57(6) 764–776
ªThe Author(s) 2020
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DOI: 10.1177/0022343320962546
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