Replication data for: Computing Nash Equilibria in Probabalistic, Multiparty Spatial Models with Nonpolicy Components

We derive conditions that guarantee the existence of a unique Nash equilibrium and develop an algorithm to compute that equilibrium inmultiparty elections with probabilistic voting, in which voters choose according to the behaviorists’ fully specified multivariate vote model.

Previously, such computations could only be approximated by laborious search methods. The algorithm, which assumes a conditional logit choice function, can be applied to spatial competition for a variety of party objectives including vote-maximization and margin-maximization, and can also encompass alternative voter policy metrics such as quadratic and linear loss functions. We show that our conditions for an equilibrium are plausible given the empirically-estimated parameters that behaviorists report for voting behavior in historical elections.