Across a wide variety of applications, the self-exciting Hawkes process has been used to model phenomena in which the history of events influences future occurrences. However, there may be many situations in which the past events only influence the future as long as they remain active. For example, a person spreads a contagious disease only as long as they are contagious. In this paper, we define a novel generalization of the Hawkes process that we call the ephemerally self-exciting process. In this new stochastic process, the excitement from one arrival lasts for a randomly drawn activity duration, hence the ephemerality. Our study includes exploration of the process itself as well as connections to well-known stochastic models such as branching processes, random walks, epidemics, preferential attachment, and Bayesian mixture models. Furthermore, we prove a batch scaling construction of general, marked Hawkes processes from a general ephemerally self-exciting model, and this novel limit theorem both provides insight into the Hawkes process and motivates the model contained herein as an attractive self-exciting process in its own right.

Multiplicative interaction models are widely used in social science to examine whether the relationship between an outcome and an independent variable changes with a moderating variable. Current empirical practice tends to overlook two important problems. First, these models assume a linear interaction effect that changes at a constant rate with the moderator. Second, estimates of the conditional effects of the independent variable can be misleading if there is a lack of common support of the moderator. Replicating 46 interaction effects from 22 recent publications in five top political science journals, we find that these core assumptions often fail in practice, suggesting that a large portion of findings across all political science subfields based on interaction models are fragile and model dependent. We propose a checklist of simple diagnostics to assess the validity of these assumptions and offer flexible estimation strategies that allow for nonlinear interaction effects and safeguard against excessive extrapolation. These statistical routines are available in both R and STATA.

Previous work on nonverbal cues has demonstrated the influence of candidates’ facial displays on voter preferences. However, the idea that visual cues affect political judgment by signaling the relative social solidarity (in-group vs. out-group status) between candidates and voters has received little attention. We fill this gap by experimentally manipulating facial cues associated with the physical features of gender and ethnicity (Afrocentric vs. Eurocentric-looking) and assessing their effects on candidate support in the context of the Italian 2013 general election. The experimental design is based on a CAWI post-election online survey conducted on a representative sample of Italian voters. We find that group differences between candidates and voters matter, but only among right of center voters, who respond more negatively to party candidates expressing “combined” (party x gender x ethnicity) dissimilarity. Gender- and ethnicity-based differences are, on the contrary, “assimilated” and accepted when the target candidate is from the voter's party.

Gender and race biases persist in western democracies, with male and white candidates still being the norm. Voters may be more inclined to express sexist and racist attitudes in countries with a traditionally male-dominated political system and a majority-white population. As sexism and racism are notoriously difficult to document, and because many people are unaware of their biases toward social groups, we bypass conventional survey measurement and observe voters’ willingness to support candidates whose physical features have been manipulated to make them appear more prototypically feminine or non-white. We implemented this approach in the context of the 2013 Italian election, by presenting a national sample of Italian voters with pictures of male and female parliamentary candidates – both unknown and well known. Overall, we found no main effects of gender or race bias in political judgment. For Italian voters, party cues are by far the most powerful indicators of out-group status, and therefore the strongest predictors of candidate perception and support. This result may be of particular interest to other political contexts characterized by strong partisan polarization.