Collaborative Research on Dynamic Models of Roll Call Voting

点名投票动态模型的协同研究

• 批准号: 0611464
• 负责人: Howard Rosenthal
• 金额: $ 9.19万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-08-01 至 2008-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0611464&HistoricalAwards=false
• 关键词: Collaborative; Research; Dynamic; Models; Roll

The public and the media commonly refer to members of the United States Congress and other legislatures as "liberals" and "conservatives". The fundamental concern of this project is to provide accurate measurement of liberal/conservatism. As a result of our development of the NOMINATE scaling algorithm in the 1980s, political scientists and economists have used our measurements of Congress in scores of professional publications and used our algorithms as measurement techniques for dozens of other legislatures, ranging from state legislatures in the United States to foreign parliaments to the United Nations General Assembly. The measurements are frequently used in teaching American political history and in introductory courses on American politics.This project increased the accuracy of measurement for Congress and updated the database current. Moreover, the work on other legislatures has suggested that the decision-making model that underpins NOMINATE does not always extend to other legislatures. Left-right (or liberal-conservative) preferences may be more sharply defined than in Congress. Abstention, as well as Yea and Nay, may be a meaningful choice. The project also provided work on estimation methods that allow for a more general approach to legislative behavior.A unique feature of our work is that its dynamic feature permits comparisons of liberal/conservatism over time. For example, others have used these measurements to study the evolution of slavery as an issue in congressional politics in the nineteenth century and trade legislation, including reciprocal tariffs and fast track, throughout American history. This dynamic feature allows us to work on models with time-dependent preferences and on supercomputing techniques for large-scale computation.

公众和媒体通常将美国国会和其他立法机构的成员称为“自由派”和“保守派”。 这个项目的基本关注点是提供自由/保守主义的准确测量。由于我们在20世纪80年代开发了NOMINATE缩放算法，政治科学家和经济学家在许多专业出版物中使用了我们对国会的测量，并将我们的算法作为其他数十个立法机构的测量技术，从美国的州立法机构到外国议会再到联合国大会。这些测量经常用于美国政治史的教学和美国政治的入门课程。该项目提高了国会测量的准确性，并更新了数据库。此外，关于其他立法机构的工作表明，支持提名的决策模式并不总是适用于其他立法机构。左翼-右翼（或自由-保守）的偏好可能比国会更明确。弃权，以及是的和不，可能是一个有意义的选择。该项目还提供了估计方法的工作，允许一个更一般的方法来立法行为。我们的工作的一个独特之处是，它的动态特征允许随着时间的推移比较自由/保守主义。例如，其他人使用这些测量方法来研究奴隶制作为19世纪国会政治问题的演变，以及整个美国历史上的贸易立法，包括互惠关税和快速通道。这种动态特性使我们能够研究具有时间依赖偏好的模型，以及用于大规模计算的超级计算技术。