Florian M. Hollenbach

Technology and Collective Action: The Effect of Cell Phone Coverage on Political Violence in Africa

The spread of cell phone technology across Africa has transforming effects on the economic and political sphere of the continent. In this paper, we investigate the impact of cell phone technology on violent collective action. We contend that the availability of cell phones as a communication technology allows political groups to overcome collective action problems more easily and improve in-group cooperation, and coordination. Utilizing novel, spatially disaggregated data on cell phone coverage and the location of organized violent events in Africa, we are able to show that the availability of cell phone coverage significantly and substantially increases the probability of violent conflict. Our findings hold across numerous different model specifications and robustness checks, including cross-sectional models, instrumental variable techniques, and panel data methods.

Ensemble Predictions of the 2012 US Presidential Election

or more than two decades, political scientists have created statistical models aimed at generating outof-sample predictions of presidential elections. In 2004 and 2008, PS: Political Science and Politics published symposia of the various forecasting models prior to Election Day. This exercise serves to validate models based on accuracy by garnering additional support for those that most accurately foretell the ultimate election outcome. Implicitly, these symposia assert that accurate models best capture the essential contexts and determinants of elections. In part, therefore, this exercise aims to develop the “best” model of the underlying data generating process. Scholars comparatively evaluate their models by setting their predictions against electoral results while also giving some attention to the models’ inherent plausibility, parsimony, and beauty. Our approach is different. Rather than creating the best model or theory, instead we create an ensemble prediction of the upcoming election. We combine the intuition, theories, and concepts implicit in all of the forecasting models presented in this symposium to make an accurate out-of-sample prediction. Without arbitrating between models and theories, we aim to aggregate them solely with an eye toward increasing our chances of getting it right. To do this, we rely on the models presented in this issue. We believe that each model captures an important set of insights about US elections. Our approach combines those insights into a single ensemble prediction. For our purposes, the theoretical differences between the models are irrelevant. All that matters is that each provides predictions for previous elections that we can use to evaluate their accuracy. We then weight each forecast by its previous performance and combine them to create the most accurate out-of-sample forecast possible that also captures the uncertainty and diversity inherent in these models.

Cabinet Formation and Portfolio Distribution in European Multiparty Systems

Government formation in multiparty systems is of self-evident substantive importance, and the subject of an enormous theoretical literature. Empirical evaluations of models of government formation tend to separate government formation per se from the distribution of key government pay-offs, such as cabinet portfolios, between members of the resulting government. Models of government formation are necessarily specified ex ante, absent any knowledge of the government that forms. Models of the distribution of cabinet portfolios are typically, though not necessarily, specified ex post, taking into account knowledge of the identity of some government ‘formateur’ or even of the composition of the eventual cabinet. This disjunction lies at the heart of a notorious contradiction between predictions of the distribution of cabinet portfolios made by canonical models of legislative bargaining and the robust empirical regularity of proportional portfolio allocations – Gamson’s Law. This article resolves this contradiction by specifying and estimating a joint model of cabinet formation and portfolio distribution that, for example, predicts ex ante which parties will receive zero portfolios rather than taking this as given ex post. It concludes that canonical models of legislative bargaining do increase the ability to predict government membership, but that portfolio distribution between government members conforms robustly to a proportionality norm because portfolio distribution follows the much more difficult process of policy bargaining in the typical government formation process.

A re-assessment of reporting bias in event-based violence data with respect to cell phone coverage

This paper discusses the issue of possible reporting bias in media-based violent-event data and its relation to the role of communication technology in fostering collective action. We expand the work of Weidmann (2016), presenting several sensitivity analyses to determine the degree to which reporting bias may confound the relationship between communication technology and violence in a recent study that relies on event data for Africa. We find no strong evidence that suggests results on the positive relationship between communication technology and collective action in the study by Pierskalla and Hollenbach (2013) are wholly an artifact of reporting bias.