Robustness of the Multidimensional Voting Model: Candidate Motivations, Uncertainty, and Convergence*
Robustness of the Multidimensional Voting Model: Candidate Motivations, Uncertainty, and Convergence*
复制标题
多维投票模型的稳健性：候选人动机、不确定性和收敛性*
DOI：
10.2307/2111212
复制
发表时间：
1985
影响因子：
4.2
通讯作者：
R. Calvert
中科院分区：
文献类型：
--
作者：
R. Calvert
这一分析表明，多维投票模型的重要影响是强大的模型的假设的重大变化。(1)如果模型中的候选人被允许对选举的政策结果部分或全部感兴趣，那么向中值的收敛仍然会发生。(2)如果候选人不确定选民的反应，因此试图最大限度地提高获胜的可能性，候选人的政纲仍然应该收敛于均衡，在弱假设下，候选人的情况对称。(3)如果这两个非标准的假设放在一起，收敛的结果不再成立;但对经典假设的微小偏离只会导致对收敛的微小偏离。结合其他最近的多维投票模型，在没有中位数的情况下，检查行为，这项研究表明，传统的模型概念化选举政治的有用性。
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.