Brian Greenhill

The perils of policy by p-value: Predicting civil conflicts

Large-n studies of conflict have produced a large number of statistically significant results but little accurate guidance in terms of anticipating the onset of conflict. The authors argue that too much attention has been paid to finding statistically significant relationships, while too little attention has been paid to finding variables that improve our ability to predict civil wars. The result can be a distorted view of what matters most to the onset of conflict. Although these models may not be intended to be predictive models, prescriptions based on these models are generally based on statistical significance, and the predictive attributes of the underlying models are generally ignored. These predictions should not be ignored, but rather need to be heuristically evaluated because they may shed light on the veracity of the models. In this study, the authors conduct a side-by-side comparison of the statistical significance and predictive power of the different variables used in two of the most influential models of civil war. The results provide a clear demonstration of how potentially misleading the traditional focus on statistical significance can be. Until out-of-sample heuristics — especially including predictions — are part of the normal evaluative tools in conflict research, we are unlikely to make sufficient theoretical progress beyond broad statements that point to GDP per capita and population as the major causal factors accounting for civil war onset.

Trade-based Diffusion of Labor Rights: A Panel Study, 1986-2002

This article investigates the nature of the linkages between trade and labor rights in developing countries. Specifically, we hypothesize that a “California effect” serves to transmit superior labor standards from importing to exporting countries, in a manner similar to the transmission of environmental standards. We maintain that, all else being equal, the labor standards of a given country are influenced not by its overall level of trade openness, but by the labor standards of its trading partners. We evaluate our hypothesis using a panel of 90 developing countries over the period 1986–2002, and we separately examine the extent to which the labor laws and the actual labor practices of the countries are influenced by those of their export destinations. We find that strong legal protections of collective labor rights in a countrys export destinations are associated with more stringent labor laws in the exporting country. This California effect finding is, however, weaker in the context of labor rights practices, highlighting the importance of distinguishing between formal legislation and actual implementation of labor rights.

Where Is the Tipping Point? Bilateral Trade and the Diffusion of Human Rights

Drawing on a panel of 136 countries over the period 1982–2004, we study a tipping point version of Vogels ‘California Effect’ in the context of the diffusion of human rights practices. Because human rights practices are often deeply embedded in a societys customs and political institutions, we expect that a high level of pressure from the importing countries is needed to bring about changes in an exporting countrys human rights records. We find strong empirical support for this threshold effect; provided that the average level of respect for human rights in importing countries is sufficiently high, trading relationships can operate as transmission belts for the diffusion of human rights practices from importing to exporting countries.

The networked peace: Intergovernmental organizations and international conflict

Existing work has shown that membership in intergovernmental organizations (IGOs) can, among other outcomes, reduce conflict, promote democratization, and shape crisis bargaining. The traditional approach to studying how IGOs can reduce conflict has focused on the effects of dyads’ direct ties to IGOs. In doing so, these analyses use fairly simple counts of the number of IGOs to which the states in each dyad share membership. We argue that this approach is too narrow; we instead consider the effects of higher-order groupings within the IGO network, which we call IGO clusters. Within these IGO clusters, states share relatively many IGO connections with each other, both directly and through indirect links through third parties, fourth parties, and so on. The effects of indirect IGO ties are especially important within such structures. We use a modularity maximization approach to detect clusters within the IGO network. We find robust empirical support for our hypothesis that the pacifying effect of IGO membership stems from the extent to which pairs of states are more deeply embedded within the wider IGO network. Indeed, we find that once we account for states’ shared membership in clusters of IGOs, the simpler dyadic measure of shared IGO membership no longer shows evidence of a conflict-inhibiting effect.