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Revisiting Group Differences in High‐Dimensional Choices: Method and Application to Congressional Speech

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  • Paul Hofmarcher
  • Jan Vavra
  • Sourav Adhikari
  • Bettina Grün

Abstract

Gentzkow, Shapiro, and Taddy, Econometrica 87, no. 4, 2019 (henceforth GST), use a supervised text‐based regression model to assess changes in partisanship in US congressional speech over time. Their estimates imply that partisanship is far greater in recent years than in the past and that it increased sharply in the early 1990s. The paper at hand provides a replication in the wide sense of GST by complementing their analysis in three ways. First, we propose an alternative unsupervised language model, which combines ideas of topic models and ideal point models, to analyze the change in partisanship over time. We apply this model to the Senate speech data used in GST ranging from 1981 to 2017. Using our model, we replicate their results on the specific evolution of partisanship. Second, our model provides additional insights such as the data‐driven estimation of evolvement of topical contents over time. Third, we identify key phrases of partisanship on topic level.

Suggested Citation

  • Paul Hofmarcher & Jan Vavra & Sourav Adhikari & Bettina Grün, 2025. "Revisiting Group Differences in High‐Dimensional Choices: Method and Application to Congressional Speech," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(5), pages 577-588, August.
    • Handle: RePEc:wly:japmet:v:40:y:2025:i:5:p:577-588
    DOI: 10.1002/jae.3125
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    References listed on IDEAS

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    1. David M. Blei & Alp Kucukelbir & Jon D. McAuliffe, 2017. "Variational Inference: A Review for Statisticians," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 859-877, April.
    2. Daniel D. Lee & H. Sebastian Seung, 1999. "Learning the parts of objects by non-negative matrix factorization," Nature, Nature, vol. 401(6755), pages 788-791, October.
    3. Feldkircher, Martin & Hofmarcher, Paul & Siklos, Pierre L., 2024. "One money, one voice? Evaluating ideological positions of euro area central banks," European Journal of Political Economy, Elsevier, vol. 85(C).
    4. Matt Taddy, 2013. "Multinomial Inverse Regression for Text Analysis," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(503), pages 755-770, September.
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