Linear Probability Models of the Demand for Attributes with an Empirical Application to Estimating the Preferences of Legislators
Linear Probability Models of the Demand for Attributes with an Empirical Application to Estimating the Preferences of Legislators
复制标题
属性需求的线性概率模型及其在估计立法者偏好方面的实证应用
DOI：
10.2307/3087459
复制
发表时间：
1996
期刊：
影响因子：
--
通讯作者：
J. Snyder
中科院分区：
文献类型：
--
作者：
J. Heckman;J. Snyder
本文制定并估计了一个严格证明的线性概率模型，该模型针对具有未观察到的属性的替代方案进行二元选择。该模型用于估计国会议员在法案投票中所表达的偏好。表征选票的属性空间的有效维度比普尔和罗森塔尔最近对国会投票的影响力研究中估计的要大。国会议员投票的不仅仅是意识形态。特定问题的属性是国会投票模式的重要决定因素。中值选民模型的估计维度太大，无法描述国会投票
This paper formulates and estimates a rigorously-justified linear probability model of binary choices over alternatives characterized by unobserved attributes. The model is applied to estimate preferences of congressmen as expressed in their votes on bills. The effective dimension of the attribute space characterizing votes is larger than what has been estimated in recent influential studies of congressional voting by Poole and Rosenthal. Congressmen vote on more than ideology. Issue-specific attributes are an important determinant of congressional" voting patterns. The estimated dimension is too large for the median voter model to describe congressional voting