This article examines how challenger parties enter the political arena and the effect of this entry by looking at the Italian 5 Star Movement (Movimento 5 Stelle – M5S). We explain the M5S's entry strategy in 2013 using the spatial approach to party competition and employing expert survey data collected for each national election between 2008 and 2018. These data allow us to analyse the changing spatial configuration of Italian politics due to the increasing salience of pro/anti-EU and pro/anti-immigration dimensions. We then apply the theoretical notion of the uncovered set (UCS) to trace how the M5S's entry reshaped the overall space of party competition, causing a realignment of existing parties. This work contributes to the ongoing debate on the electoral success of challenger parties and the emerging cleavages and polarization of party systems in Western European countries.

Social choice theory demonstrates that majority rule is generically indeterminate. However, from an empirical perspective, large and arbitrary policy shifts are rare events in politics. The uncovered set (UCS) is the dominant preference-based explanation for the apparent empirical predictability of majority rule in multiple dimensions. Its underlying logic assumes that voters act strategically, considering the ultimate consequences of their actions. I argue that all empirical applications of the UCS rest on an incomplete behavioral model assuming purely egoistically motivated individuals. Beyond material self-interest, prosocial motivations offer an additional factor to explain the outcomes of majority rule. I test my claim in a series of committee decision-making experiments in which I systematically vary the fairness properties of the policy space while keeping the location of the UCS constant. The experimental results overwhelmingly support the prosociality explanation.

We consider the uncovered set (i.e. the complement of the union of growing random intervals) in the one-dimensional Johnson-Mehl model. Let S(z,L) be the number of components of this set at time z > 0 which intersect (0, L]. An explicit bound is known for the total variation distance between the distribution of S(z,L) and a Poisson distribution, but due to clumping of the components the bound can be rather large. We here give a bound for the total variation distance between the distribution of S(z,L) and a simple compound Poisson distribution (a Pólya-Aeppli distribution). The bound is derived by interpreting S(z,L) as the number of visits to a ‘rare’ set by a Markov chain, and applying results on compound Poisson approximation for Markov chains by Erhardsson. It is shown that under a mild condition, if z→∞ and L→∞ in a proper fashion, then both the Pólya-Aeppli and the Poisson approximation error bounds converge to 0, but the convergence of the former is much faster.