Nonparametric Ideal-Point Estimation and Inference. (8th March 2018)

• Record Type: Journal Article
• Authors: Tahk, Alexander
• Is Part Of: Political analysis. Volume 26:Number 2(2018)
• Page Start: 131
• Page End: 146
• Publication Date: 2018-03-08
• Subjects: ideal-point estimation, -- hypothesis testing, -- nonparametric analysis, -- nonparametric estimation; Political science -- Methodology -- Periodicals; Electronic journals; 320.011
• DOI: 10.1017/pan.2017.38
• Languages: English
• ISSNs: 1047-1987

Abstract

Abstract : Existing approaches to estimating ideal points offer no method for consistent estimation or inference without relying on strong parametric assumptions. In this paper, I introduce a nonparametric approach to ideal-point estimation and inference that goes beyond these limitations. I show that some inferences about the relative positions of two pairs of legislators can be made with minimal assumptions. This information can be combined across different possible choices of the pairs to provide estimates and perform hypothesis tests for all legislators without additional assumptions. I demonstrate the usefulness of these methods in two applications to Supreme Court data, one testing for ideological movement by a single justice and the other testing for multidimensional voting behavior in different decades.