Econometrica

Journal Of The Econometric Society

An International Society for the Advancement of Economic
Theory in its Relation to Statistics and Mathematics

Edited by: Guido W. Imbens • Print ISSN: 0012-9682 • Online ISSN: 1468-0262

Econometrica: Jul, 2019, Volume 87, Issue 4

Measuring Group Differences in High-Dimensional Choices: Method and Application to Congressional Speech

https://doi.org/10.3982/ECTA16566
p. 1307-1340

Matthew Gentzkow, Jesse M. Shapiro, Matt Taddy

We study the problem of measuring group differences in choices when the dimensionality of the choice set is large. We show that standard approaches suffer from a severe finite‐sample bias, and we propose an estimator that applies recent advances in machine learning to address this bias. We apply this method to measure trends in the partisanship of congressional speech from 1873 to 2016, defining partisanship to be the ease with which an observer could infer a congressperson's party from a single utterance. Our estimates imply that partisanship is far greater in recent years than in the past, and that it increased sharply in the early 1990s after remaining low and relatively constant over the preceding century.


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Supplement to "Measuring Group Differences in High-Dimensional Choices: Method and Application to Congressional Speech"

This zip file contains replication files for the manuscript, and an online appendix that contains material not found within the manuscript.