Spatial voting models of legislators' preferences are used in political science to test theories about their voting behavior. These models posit that legislators' ideologies as well as the ideologies reflected in votes for and against a bill or measure exist as points in some low dimensional space, and that legislators vote for positions that are close to their own ideologies. Bayesian spatial voting models have been developed to test sharp hypotheses about whether a legislator's revealed ideal point differs for two distinct sets of bills. This project extends such a model to identify covariates that explain whether legislators exhibit such differences in ideal points. We use our method to examine voting behavior on procedural versus final passage votes in the U.S. house of representatives for the 93rd through 113th congresses. The analysis provides evidence that legislators in the minority party as well as legislators with a moderate constituency are more likely to have different ideal points for procedural versus final passage votes.

翻译：政治学中利用立法者偏好的空间投票模型来检验有关其投票行为的理论。这些模型假设立法者的意识形态以及支持或反对某项议案或措施所体现的意识形态存在于某个低维空间中的点，并且立法者倾向于投票支持与其自身意识形态接近的立场。贝叶斯空间投票模型已被开发用于检验关于立法者在两组不同议案中展现的揭示性理想点是否存在差异的严格假设。本项目将此类模型进行扩展，以识别能够解释立法者是否在理想点上呈现此类差异的协变量。我们运用所提方法考察美国众议院第93届至第113届国会中程序性投票与最终通过投票之间的投票行为。分析表明，少数派政党立法者以及拥有温和选民群体的立法者更可能在程序性投票与最终通过投票中表现出不同的理想点。