Fast Estimation of Ideal Points with Massive Data

Volume: 110, Issue: 4, Pages: 631 - 656
Published: Nov 1, 2016
Abstract
Estimation of ideological positions among voters, legislators, and other actors is central to many subfields of political science. Recent applications include large data sets of various types including roll calls, surveys, and textual and social media data. To overcome the resulting computational challenges, we propose fast estimation methods for ideal points with massive data. We derive the expectation-maximization (EM) algorithms to estimate...
Paper Details
Title
Fast Estimation of Ideal Points with Massive Data
Published Date
Nov 1, 2016
Volume
110
Issue
4
Pages
631 - 656
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