Quarterly Journal of Political Science > Vol 19 > Issue 4

Parsing Party Polarization in Congress

Daniel J. Moskowitz, University of Chicago, USA, dmoskowitz@uchicago.edu , Jon C. Rogowski, University of Chicago, USA, jrogowski@uchicago.edu , James M. Snyder Jr., Harvard University and NBER, USA, jsnyder@gov.harvard.edu
 
Suggested Citation
Daniel J. Moskowitz, Jon C. Rogowski and James M. Snyder Jr. (2024), "Parsing Party Polarization in Congress", Quarterly Journal of Political Science: Vol. 19: No. 4, pp 357-385. http://dx.doi.org/10.1561/100.00022039

Publication Date: 16 Oct 2024
© 2024 D. J. Moskowitz, J. C. Rogowski and J. M. Snyder, Jr.
 
Subjects
Congress,  Political parties
 
Keywords
Congresspolitical partiesideological polarization
 

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In this article:
Congressional Polarization: Empirical and Conceptual Issues 
Potential Explanations for Rising Polarization 
Data and Measures 
Results: Do Legislators Change Positions Over Time? 
Conclusion 
References 

Abstract

A vast literature documents growing ideological divisions between the parties in the contemporary U.S. Congress based on estimates from roll-call voting behavior (such as DW-NOMINATE). We revisit theoretical and empirical claims about the nature of partisan polarization by addressing concerns raised in recent scholarship about the comparability and interpretation of roll-call estimates over time. We leverage data from candidate surveys that allow us to hold the policy agenda constant from 1996 to 2008. We show that the replacement of relatively moderate legislators with more ideologically extreme legislators, particularly among Republicans, explains virtually all of the recent growth in partisan polarization. We further demonstrate that these patterns are explained mostly by increased polarization over social and environmental issues and link our findings to changes in the congressional agenda. Our results have important substantive and methodological implications for evaluating sources of legislative polarization and using roll-call measures in empirical applications.

DOI:10.1561/100.00022039

Online Appendix | 100.00022039_app.pdf

This is the article's accompanying appendix.

DOI: 10.1561/100.00022039_app

Replication Data | 100.00022039_supp.zip (ZIP).

This file contains the data that is required to replicate the data on your own system.

DOI: 10.1561/100.00022039_supp