Measuring Polarization in High-Dimensional Data: Method and Application to Congressional Speech

Matthew Gentzkow (), Jesse Shapiro and Matt Taddy ()

Working Papers from eSocialSciences

Abstract: This paper studies trends in the partisanship of Congressional speech from 1873 to 2009. It defines partisanship to be the ease with which an observer could infer a congressperson’s party from a fixed amount of speech, and estimates it using a structural choice model and methods from machine learning. This paper applies tools from structural estimation and machine learning to study the partisanship of language in the US Congress. [Working Paper 22423]

Keywords: Polarization; Congressional Speech; Democrats; Republicans; Affordable Care Act; Partisanship (search for similar items in EconPapers)
Date: 2016-07
Note: Institutional Papers
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Citations: View citations in EconPapers (40)

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