Characterization of multidimensional spatial models of elections with a valence dimension

Spatial models of political competition are typically based on two assumptions. One is that all the voters identically perceive the platforms of the candidates and agree about their score on a "valence" dimension. The second is that each voter's preferences over policies are decreasing in the distance from that voter's ideal point, and that valence scores enter the utility function in an additively separable way. The goal of this paper is to examine the restrictions that these two assumptions impose, starting from a more primitive (and observable) data. Specifically, we consider the case where only the ideal point in the policy space and the ranking over candidates are known for each voter. We provide necessary and su±cient conditions for this collection of preference relations to be consistent with utility maximization as in the standard models described above. That is, we characterize the case where there are policies x1,...,xm for the m candidates and numbers v1,...,vm representing valence scores, such that a voter with an ideal policy y ranks the candidates according to vi-||xi-y||^2.