Introduction
| Date | 01 March 2017 |
| Author | Nils W Metternich,Håvard Mokleiv Nygård,Julian Wucherpfennig,Håvard Hegre |
| Published date | 01 March 2017 |
| DOI | 10.1177/0022343317691330 |
| Subject Matter | Introduction |
Introduction
Introduction: Forecasting in peace research
Håvard Hegre
Uppsala University & Peace Research Institute Oslo (PRIO)
Nils W Metternich
Department of Political Science, University College London
Håvard Mokleiv Nygård
Peace Research Institute Oslo (PRIO)
Julian Wucherpfennig
Hertie School of Governance
Abstract
Prediction and forecasting have now fully reached peace and conflict research. We define forecasting as predictions
about unrealized outcomes given model estimates from realized data, and predictions more generally as the assign-
ment of probability distributions to realized or unrealized outcomes. Increasingly, scholars present within- and out-
of-sample prediction results in their publications and sometimes even forecasts for unrealized, future outcomes. The
articles in this special issue demonstrate the ability of current approaches to forecast events of interest and contributes
to the formulation of best practices for forecasting within peace research. We highlight the role of forecasting for
theory evaluation and as a bridge between academics and policymakers, summarize the contributions in the special
issue, and provide some thoughts on how research on forecasting in peace research should proceed. We suggest some
best practices, noting the importance of theory development, interpretability of models, replicability of results, and
data collection.
Keywords
forecasting, out of sample evaluation, peace research, prediction, theory testing
No matter how I turn it over in my mind, the number
one task of peace research always turns out to be that of
prediction [...] (J David Singer, 1973)
Although rarely articulated explicitly, ultimately being
able to forecast peace and conflict is a fundamental moti-
vation for peace research (Singer, 1973). Indeed, reliable
forecasting or early-warning systems that could indicate
risks before conflict erupts or escalates would make it
possible to prepare for, intervene in, or build resilience
against deadly conflicts (Harff, 2003). Moreover, by
designing forecasts as contingent on policy interventions,
they could be powerfultools to guide policy: by comparing
forecasts of the expected risk or intensity of armed con-
flict given different conflict-preventing policies, the risks
associated with particular interventions can be more
fully understood, and the case for (non-)intervention
made evidence based.
Forecasting peace and conflict was long viewed with
considerable skepticism and often considered unfeasible
(e.g. Stephens, 2012). However, new data projects, new
theories, and innovative methods – as demonstrated in
this special issue – are taking us closer to generating
conflict forecasts that are sufficiently precise to be policy
relevant. We focus on forecasts of phenomena that are
sufficiently regular and frequent to support the
Corresponding author:
havard.hegre@pcr.uu.se
Journal of Peace Research
2017, Vol. 54(2) 113–124
ªThe Author(s) 2017
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DOI: 10.1177/0022343317691330
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