Scholars and practitioners in international relations have a strong interest in forecasting international conflict. However, due to the complexity of forecasting rare events, existing attempts to predict the onset of international conflict in a cross-national setting have generally had low rates of success. In this paper, we apply Bayesian methods to develop a forecasting model designed to predict the onset of international conflict at the yearly level. We find that this model performs substantially better at producing accurate predictions both in and out of sample.
BeckNKingGZengL.Improving quantitative studies of international conflict: a conjecture. Am Political Sci Rev2000; 94: 21–35.
2.
BeckNKingGZengL.Theory and evidence in international conflict: a response to de Marchi, Gelpi, and Grynaviski. Am Political Sci Rev2004; 98: 379–389.
3.
GleditschKSWardMD.Forecasting is difficult, especially about the future: using contentious issues to forecast interstate disputes. J Peace Res2013; 50: 17–31.
4.
De MarchiSGelpiCGrynaviskiJD. Untangling neural nets. Am Political Sci Rev2004; 98: 371–378.
5.
FearonJ.Rationalist explanations for war. Int Organiz1995; 49: 379–414.
6.
PowellR.War is a commitment problem. Int Organiz2006; 60: 169–203.
7.
CopelandDC.The origins of major war. Ithaca, NY: Cornell University Press, 2000.
8.
GilpinR.War and change in world politics. Cambridge: Cambridge University Press, 1983.
9.
KennedyP.The rise and fall of the great powers. New York: Vintage, 2010.
10.
DebsAMonteiroNP.Known unknowns: power shifts, uncertainty, and war. Int Organiz2014; 68: 1–31.
11.
SingerJDBremerSStuckeyJ.Capability distribution, uncertainty, and major power war, 1820–1965. In: RussettBM (ed) Peace, war, and numbers. Sage Publications, 1972.
12.
GiblerDMRiderTJHutchisonML.Taking arms against a sea of troubles: conventional arms races during periods of rivalry. J Peace Res2005; 42: 131–147.
13.
JervisR.Perception and misperception in international politics. Princeton, NJ: Princeton University Press, 1976.
14.
RiderTJFindleyMGDiehlPF.Just part of the game? Arms races, rivalry, and war. J Peace Res2011; 48: 85–100.
15.
BremerSA.Dangerous dyads conditions affecting the likelihood of interstate war, 1816–1965. J Conflict Resolut1992; 36: 309–341.
16.
GartzkeEKroenigM.Nukes with numbers: empirical research on the consequences of nuclear weapons for international conflict. Annu Rev Political Sci2016; 19: 397–412.
17.
WaltzKN.Nuclear myths and political realities. Am Political Sci Rev1990; 84: 731–745.
18.
Bueno de MesquitaBMorrowJDSiversonRM, et al. The logic of political survival. Cambridge, MA: MIT Press, 2003.
19.
OnealJRRussettBM.Clear and clean: the fixed effects of the liberal peace. Int Organiz2001; 55: 469–485.
20.
PecenyMBeerCCSanchez-TerryS.Dictatorial peace?Am Political Sci Rev2002; 96: 15–26.
21.
MarshallMGJaggersK.Political regime characteristics and transitions, 1800–2012. Polity IV Project, 2013;
22.
GiblerDMSarkeesMR.Measuring alliances: the Correlates of War Formal Interstate Alliance Dataset, 1816–2000. J Peace Res2004; 41: 211–222.
23.
MaozZ.Pacifism and fightaholism in international politics: a structural history of national and dyadic conflict, 1816–1992. Int Stud Rev2004; 6: 107–133.
24.
MitchellSMHenselPR.International institutions and compliance with agreements. Am J Political Sci2007; 51: 721–737.
25.
PevehouseJNordstromTWarnkeK. The Correlates of War 2 international governmental organizations data version 2.0. Conflict Manage Peace Sci2004; 21: 101–119.
26.
GiblerDMMillerSVLittleEK.An analysis of the militarized interstate dispute (MID) dataset, 1816–2001. Int Stud Q2016; 60: 719–730.
27.
PalmerGD’OrazioVKenwickM, et al. The MID4 dataset, 2002–2010: procedures, coding rules and description. Conflict Manage Peace Sci2015; 32: 222–242.
28.
JenkeLGelpiC.Theme and variations: historical contingencies in the causal model of interstate conflict. J Conflict Resolut201761: 2262-2284 .
29.
KingGZengL.Explaining rare events in international relations. Int Organiz2001; 55: 693–715.
30.
GelmanAJakulinAPittauMG, et al. A weakly informative default prior distribution for logistic and other regression models. Ann Appl Stat2008; 2: 1360–1383.
31.
GreenhillBWardMDSacksA.The separation plot: a new visual method for evaluating the fit of binary models. Am J Political Sci2011; 55: 991–1002.
32.
BrandtPTFreemanJRSchrodtPA.Real time, time series forecasting of inter- and intra-state political conflict. Conflict Manage Peace Sci2011Feb1; 28(1):41–64.
