Major powers signal support for protégés in order to reassure them and deter harm against them. Yet, it is not always clear how to identify who a major power's protégés are or the degree of support signaled. Major powers have a variety of complementary signals to choose among, including alliances, arms transfers, joint military exercises, and others. It can be difficult to weigh the importance of individual signals, especially since different major powers do not deploy each signal in the same way. We address this challenge using a Bayesian latent measurement model, which provides a theoretically coherent means of identifying the overall level of support signaled by a major power for a protégé. Our approach yields a cross-sectional time-series dataset, providing a continuous measure of the degree of support signaled by major powers for all minor powers from 1950 to 2012. Our model also provides insights regarding which signals of support are most informative when sent by each major power. We find considerable variation among major powers regarding which of their signals are most meaningful, but in general alliances and military exercises tend to be among the most important signals. In further applications using our latent measure, we also assess under which conditions major powers are likely to increase their signals of support for protégés, as well as predict whether a major power will intervene in conflicts involving its protégés.

Several scholars argue that systemic global trends are pulling individuals not only upward toward the global level, but also downward to the local level; the result is a potential loss of authority for the state (Ferguson and Mansbach 2004;Rosenau 1990). Their theory of "fragmegration" can provide a causal mechanism for why longstanding grievances may erupt into civil war at a particular time. While increased global exposure does provide both states and individual citizens with tremendous benefits, sudden "shocks" of globalization can overwhelm a state's capacity to offset the negative impacts of globalization, thus weakening a state's capacity to deal with rival polities for the allegiance of its citizens. The present study conducts a cross-sectional logistic regression with discrete duration analysis to test the impact of globalization shocks on the onset of civil wars between the years 1970-1999. The results demonstrate that increasingly dramatic changes in the level of global integration are associated with an increased risk of civil war onset.

The strategic nature of political interactions has long captured the attention of political scientists. A traditional statistical approach to modeling strategic interactions involves multi-stage estimation, which improves parameter estimates associated with one stage by using the information from other stages. The application of such multi-stage approaches, however, imposes rather strict demands on data availability: data on the dependent variable must be available for each strategic actor at each stage of the interaction. Limited or no data make such approaches difficult or impossible to implement. Political science data, however, especially in the fields of international relations and comparative politics, are not always structured in a manner that is conducive to these approaches. For example, we observe and have plentiful data on the onset of civil wars, but not the preceding stages, in which opposition groups decide to rebel or governments decide to repress them. In this article, I derive an estimator that probabilistically estimates unobserved actor choices related to earlier stages of strategic interactions. I demonstrate the advantages of the estimator over traditional and split-population binary estimators both using Monte Carlo simulations and a substantive example of the strategic rebel–government interaction associated with civil wars.

Building on economic norms theory, I argue that the causes of international conflict may be contextual rather than constant over time. I explore the temporal patterns in the predictors of conflict in data on European conflict between 1870 and 2001, using an endogenous Markov chain Monte Carlo Poisson change-point model. I find that the period can be divided into two time periods, different in terms of the direction of the effect of the main conflict predictors. While democracy has a positive effect on conflict in the period between 1870 and 1938, it has a negative effect from 1938 to 2001. Likewise, trade initially has no impact on conflict, but later exerts a pacifying effect. Post-estimation analyses suggest that such patterns are best explained by the externalization of contractual norms, which is consistent with economic norms theory.

We argue that democratic institutions influence property rights in attracting foreign direct investment (FDI) by providing: (1) a coherent logic to the property rights regime that is created in a state and (2) a legitimate way to manage conflicts that arise in dynamic economies. We expect that the marginal effect of property rights in attracting FDI has increased over time with the rate of technological dynamism. We test this using a non-nested multilevel modeling strategy with random coefficients on data from 1970 to 2009. Our results demonstrate that the effect of property rights on attracting FDI is contingent on democratic institutions and that this effect becomes more pronounced over time. This effect holds for both developing and developed countries across all regions.