A Day by Day Measure of Legislator Ideology: Non-Parametric Smoothing of Legislator Ideal Points with Optimal Classification

40 Pages Posted: 1 Feb 2010

Date Written: April 27, 2009

Abstract

This paper presents a method of adapting Poole’s Optimal Classification to smooth ideal points by recovering legislator estimates from localized subsets of the data. Each legislator trend consists of a series of localized kernel estimates, one for each roll call on which the legislator casts a vote. In contrast to the only widely used estimation technique that allows for inter-temporal movement of ideal points, McCarty, Poole, and Rosenthal's DW-NOMINATE, the method presented measures time by the exact date of the roll call rather than by a single integer value for each two-year Congress. The method also does not constrain inter-temporal movement to polynomial functions of time. The result is a set of LOESS-like trends that describe legislator movement through time, thus marking the first roll-call scaling method capable of summarizing legislator movement within and across legislative periods. I illustrate with scalings of the US Senate and the French Fourth Republic.

Keywords: Ideal Point Estimation, Optimal Classification, Ideology, Smoothing, US Senate

Suggested Citation

Bonica, Adam, A Day by Day Measure of Legislator Ideology: Non-Parametric Smoothing of Legislator Ideal Points with Optimal Classification (April 27, 2009). Available at SSRN: https://ssrn.com/abstract=1396022 or http://dx.doi.org/10.2139/ssrn.1396022

Adam Bonica (Contact Author)

Stanford University ( email )

Stanford, CA 94305
United States

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