# Robustness of the Multidimensional Voting Model: Candidate Motivations, Uncertainty, and Convergence*

**Randall L. Calvert**

CiteWeb id: 20160000068

CiteWeb score: 594

This analysis demonstrates that important implications of the multidimensional voting model are robust to significant changes in the model's assumptions. (1) If candidates in the model are allowed to be partially or totally interested in the election's policy outcomes, convergence to the median must still occur. (2) If candidates are uncertain about voters' responses, and therefore attempt to maximize the probability of winning, the candidate platforms should still converge in equilibrium under weak assumptions about symmetry of the candidates' situations. (3) If both of these nonstandard assumptions are made together, the convergence result no longer holds; but small departures from the classic assumptions lead to only small departures from convergence. In combination with other recent multidimensional voting models that examine behavior in the absence of a median, this study indicates the usefulness of the traditional model for conceptualizing electoral politics.

**Robustness of the Multidimensional Voting Model: Candidate Motivations, Uncertainty, and Convergence***" is placed in the Top 100 in 2016.

Randall L. Calvert,

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