Bear F. Braumoeller

Hypothesis Testing and Multiplicative Interaction Terms

When a statistical equation incorporates a multiplicative term in an attempt to model interaction effects, the statistical significance of the lower-order coefficients is largely useless for the typical purposes of hypothesis testing. This fact remains largely unappreciated in political science, however. This brief article explains this point, provides examples, and offers some suggestions for more meaningful interpretation.I am grateful to Tim McDaniel, Anne Sartori, and Beth Simmons for comments on a previous draft.

Systemic Politics and the Origins of Great Power Conflict

Systemic theories of international politics rarely predict conflict short of cataclysmic systemic wars, and dyadic theories of conflict lack systemic perspective. This article attempts to bridge the gap by introducing a two-step theory of conflict among Great Powers. In the first stage, states engage in a dynamic, ongoing process of managing the international system, which inevitably produces tensions among them. In the second stage, relative levels of security-related activity determine how and when those tensions erupt into disputes. A test of the theory on Great Power conflicts from the nineteenth century supports the argument and, moreover, favors the deterrence model over the spiral model as a proximate explanation of conflict in the second stage.

Political Irrelevance, Democracy, and the Limits of Militarized Conflict

Although the statistical literature on conflict studies has generated strong and consistent findings on the relationship of political irrelevance and dyadic democracy to conflict, scholars have paid scant attention to the interesting theoretical issue of how they matter. The authors argue that additive controls and dropping irrelevant dyads constitute misspecifications of their effects. There are theoretical reasons to believe that the impact of distance on conflict is not sufficiently severe to justify the practice of simply dropping irrelevant dyads. Moreover, they argue that political irrelevance and dyadic democracy, rather than subtracting some constant quantity, interact to impose an upper bound on the probability of conflict initiation. They find both of these arguments to be supported in a reanalysis of a prominent study of dispute initiation.

The promise of historical dynamism for the American study of international relations

While The Global Transformation makes a compelling case for the importance of the oft-ignored 19th century for IR theory, the book also represents an opportunity for an audience for which it was probably not intended: American IR scholars working in the quantitative empirical tradition, whom it should prompt to re-think the question of how the interactions that they seek to understand are conditional on deeper material and ideational dynamics.

Aggregation Bias and the Analysis of Necessary and Sufficient Conditions in fsQCA

Fuzzy-set qualitative comparative analysis (fsQCA) has become one of the most prominent methods in the social sciences for capturing causal complexity, especially for scholars with small- and medium-N data sets. This research note explores two key assumptions in fsQCA’s methodology for testing for necessary and sufficient conditions—the cumulation assumption and the triangular data assumption—and argues that, in combination, they produce a form of aggregation bias that has not been recognized in the fsQCA literature. It also offers a straightforward test to help researchers answer the question of whether their findings are plausibly the result of aggregation bias.