We study rare events data, binary dependent variables with dozens to thousands of times fewer ones (events, such as wars, vetoes, cases of political activism, or epidemiological infections) than zeros (“nonevents”). In many literatures, these variables have proven difficult to explain and predict, a problem that seems to have at least two sources. First, popular statistical procedures, such as logistic regression, can sharply underestimate the probability of rare events. We recommend corrections that outperform existing methods and change the estimates of absolute and relative risks by as much as some estimated effects reported in the literature. Second, commonly used data collection strategies are grossly inefficient for rare events data. The fear of collecting data with too few events has led to data collections with huge numbers of observations but relatively few, and poorly measured, explanatory variables, such as in international conflict data with more than a quarter-million dyads, only a few of which are at war. As it turns out, more efficient sampling designs exist for making valid inferences, such as sampling all available events (e.g., wars) and a tiny fraction of nonevents (peace). This enables scholars to save as much as 99 % of their (nonfixed) data collection costs or to collect much more meaningful explanatory

This paper extends earlier work on the application of hidden Markov models (HMMs) to the problem of forecasting international conflict. HMMs are a sequence comparison method widely used in computerized speech recognition as a computationally efficient method of generalizing a set of sequences observed in a noisy environment. The technique is easily be adapted to work with \international event data. The paper provides a theoretical "micro-foundation" for the use of sequence comparison in conflict early-warning based on coadaptation of organizational standard operating procedures. The left-right (LR) HMM used in speech recognition is first extended to a left-right-left (LRL) model that allows a crisis to escalate and de-escalate. This model is tested for its ability to correctly discriminate between BCOW crisis that involve and do not involve war. The LRL model provides slightly more accurate classification than the LR model. The interpretation of the hidden states in the LRL models, how...

Some of the most important phenomena in international conflict are coded as "rare events data," binary dependent variables with dozens to thousands of times fewer events, such as wars, coups, etc., than "nonevents". Unfortunately, rare events data are difficult to explain and predict, a problem that seems to have at least two sources. First, and most importantly, the data collection strategies used in international conflict are grossly inefficient. The fear of collecting data with too few events has led to data collections with huge numbers of observations but relatively few, and poorly measured, explanatory variables. As it turns out, more efficient sampling designs exist for making valid inferences, such as sampling all available events (e.g., wars) and a tiny fraction of non-events (peace). This enables scholars to save as much as 99% of their (non-fixed) data collection costs, or to collect much more meaningful explanatory variables. Second, logistic regression, and other commonly ...

We conducted an experimental test of spiraling behavior in a simulated crisis situation. We investigated the relationship between weapons= acquisition and the likelihood of engaging in aggressive behavior, such as going to war. The sample included 100 male and female subjects who participated in a crisis simulation in same-sex dyads

The oldest answered question in the social sciences is `Why do societies collapse?'. I advance a theory of the collapse of societies that is based on self-organized criticality, which is a nonlinear process that produces sudden shifts and fractal patterns in historical time series. More generally, I conjecture that weak, self-organized criticality is ubiquitous in human systems. If this conjecture is correct, it would not only explain the source of total societal collapses but the pattern of most other sorts of human calamities and even the frequency distribution of many mundane day-to-day events. KEY WORDS. nonlinear dynamics. self-organized criticality. societies. theories of history. time series Perhaps the oldest unresolved question in social science is `Why do societies collapse?'. The literature on the topic is immense. It ranges from moralistic comments in ancient texts about the destruction of Sodom and Gomorrah, to Augustine's The City of God (410), Edward Gibbon's Decline and Fall

of Foreign Policy Decision-making The aim of this paper is to introduce systemic analysis in poliheuristic method of foreign policy decision-making analysis. It starts with theoretical review, and assessment of strengths and weaknesses of poliheuristic method, as developed by Mintz et. al. The paper proposes certain changes and/or amendments to the theory, and calls for better integration of this decision-making theory with other IR theories dealing with state behaviour in the international system. A hypothesis and potential tests are proposed and the paper ends with bibliography. Foreign policy analysis is an important area of the discipline of international relations. It deals with ongoing concerns in the international arena as it tries to systematically communicate pros and cons of certain policy decisions. It is very difficult to develop a robust theory that could encompass all areas of foreign policy, as issues emerge and disappear, events take different forms and shapes, and decision-makers come and go (at least in democratic countries). It should be quite possible; however, to build a consistent analytical mode for a specific area of foreign policy – in this case, decision-making. Decision-making is at heart of every foreign policy issue, as governments and state leaders

This paper examines whether the expected utility theory of war explains international conflict equally well across all regions and time-periods as a way of examining whether instrumental rationality is a universal phenomenon. In the rational choice literature, scholars typically assume that decision-makers are purposive egoistic decision-makers with common preferences across various outcomes. However, critics of the assumption have suggested that preferences and decision structures vary as a function of polity type, culture and learning among state leaders. However, there have been few attempts to directly examine this assumption and evaluate whether it seems empirically justified. In this paper we attempt to test the assumption of instrumental rationality, examining several competing hypotheses about the nature of decision making in international relations and expectations about where and when instrumental rationality should be most readily observable. In particular, we want to explor...

Despite immense data collections, prestigious journals, and sophisticated analyses, empirical findings in the literature on international conflict are frequently unsatisfying. Statistical results appear to change from article to article and specification to specification. Very few relationships hold up to replication with even minor respecification. Accurate forecasts are nonexistent. We provide a simple conjecture about what accounts for this problem, and offer a statistical framework that better matches the substantive issues and types of data in this field. Our model, a version of a "neural network" model, forecasts substantially better than any previous effort, and appears to uncover some structural features of international conflict. 1 Introduction Despite immense data collections, prestigious journals, and sophisticated analyses, empirical findings in the literature on international conflict are frequently unsatisfying. Statistical results appear to change from article to arti...

In this paper, we review the central claim of a growing literature: that is, that democratic states rarely, if ever, wage war against and are very unlikely to engage in militarized disputes with other democratic states. We fkst examine the analytic foundations of this claim. We conclude that they are tenuous. Next, we examine the evidence.

We examine whether the conditions affecting initial expressions of hostility are similar to those affecting militarized disputes, which are not only more serious but also represent subsequent stages in the conflict process. Using data on dyadic interactions covering the 1951-1992 period, we estimate two models, one designed to take into account selection effects and the other allowing for conjunctive causation. Both provide closer approximations to theoretical models of the conflict process, and both yield similar results. Overall, our findings correspond with Kant's understanding that all states are subject to the realist conditions of interstate competition that makes disputes likely, but that the liberal influences, where present, can constrain the escalation of such disputes to war. The investigation also provides support for our argument that the effects of various influences on the conflict process are nonmonotonic over the range of hostile state behavior. We find that geopolitical factors affecting the opportunity for conflict are relatively more important in earlier stages of the conflict process, when less information is available regarding acceptable settlements and the resolve of actors to achieve them, than in later stages. By contrast, the importance of factors affecting willingness -- democratic norms and institutions and economic interdependence -- increase as the conflict process unfolds because they facilitate the flow of information relevant to the ongoing dispute. Fortunately, militarized conflict between states is rare. Nevertheless, diplomatic and other forms of low-level interstate conflict surely are not rare and these have the potential to escalate to more violent forms of dispute -- so scholars and policymakers have great interest in the tools o...