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Policy and the structure of roll call voting in the US house

Published online by Cambridge University Press:  27 March 2020

Scott de Marchi Open the ORCID record for Scott de Marchi [Opens in a new window] ,
Spencer Dorsey  and
Michael J. Ensley
Scott de Marchi*
Affiliation:
Department of Political Science, Duke University, NC, USA
Spencer Dorsey
Affiliation:
Department of Political Science, Duke University, NC, USA
Michael J. Ensley
Affiliation:
Department of Political Science, Kent State University, OH, USA
*
*Corresponding author. E-mail: demarchi@duke.edu
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Abstract

Competition in the US Congress has been characterised along a single, left-right ideological dimension. We challenge this characterisation by showing that the content of legislation has far more predictive power than alternative measures, most notably legislators’ ideological positions derived from scaling roll call votes. Using a machine learning approach, we identify a topic model for final passage votes in the 111th through the 113th House of Representatives and conduct out-of-sample tests to evaluate the predictive power of bill topics relative to other measures. We find that bill topics and congressional committees are important for predicting roll call votes but that other variables, including member ideology, lack predictive power. These findings raise serious doubts about the claim that congressional politics can be boiled down to competition along a single left-right continuum and shed new light on the debate about levels of polarisation in Congress.

Keywords

congressideologymachine learningNOMINATEpredictiontopic modelling
Type
Research Article
Information
Journal of Public Policy , Volume 41 , Issue 2 , June 2021 , pp. 384 - 408
Copyright
© The Author(s) 2020. Published by Cambridge University Press

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References

Adler, ES and Wilkerson, JD (2013) Congress and the Politics of Problem Solving. New York, NY: Cambridge University Press.Google Scholar
Aldrich, JH (1995) Why Parties? The Origin and Transformation of Political Parties in America. Chicago, IL: The University of Chicago Press.CrossRefGoogle Scholar
Aldrich, JH, Montgomery, JM and Sparks, DB (2014) Polarization and Ideology: Partisan Sources of Low Dimensionality in Scaled Roll Call Analyses. Political Analysis 22: 435–456.CrossRefGoogle Scholar
Anderson, SE (2012) Policy Domain-Specific Ideology: When Interest Group Scores Offer More Insight. Politics & Policy 40(6): 1186–1202.CrossRefGoogle Scholar
Bateman, DA, Clinton, JD and Lapinski, JS (2017) A House Divided? Roll Calls, Polarization, and Policy Differences in the U.S. House, 1877–2011. American Journal of Political Science 61(3): 698–714.CrossRefGoogle Scholar
Bishop, CM (1995) Neural Networks for Pattern Recognition. New York, NY: Clarendon Press.Google Scholar
Carmines, EG and Stimson, JA (1989) Issue Evolution: Race and the Transformation of American Politics. Princeton, NJ: Princeton University Press.CrossRefGoogle Scholar
Carson, J, Finocchiaro, C and Rohde, D (2010) Consensus, Conflict, and Partisanship in House Decision Making: A Bill-Level Examination of Committee and Floor Behavior. Congress and the Presidency 37(3): 231–253.CrossRefGoogle Scholar
Clinton, JD (2006) Representation in Congress: Constituents and Roll Calls in the 106th House. Journal of Politics, 68(2): 397–409.CrossRefGoogle Scholar
Clinton, JD (2012) Using Roll Call Estimates to Test Models of Politics. Annual Review of Political Science, 15(1): 79–99.CrossRefGoogle Scholar
Clinton, JD (2017) Coding the Ideological Direction and Content of Policies. Annual Review of Political Science, 20(1): 433–450.CrossRefGoogle Scholar
Conn, D and Ramirez, CM (2016) Random Forests and Fuzzy Forests in Biomedical Research. In Alvarez, RM (ed.), Computational Social Science. New York, NY: Cambridge University Press.Google Scholar
Cox, GW and McCubbins, MD (1993) Legislative Leviathan. Berkeley, CA: University of California Press.Google Scholar
Cox, GW and McCubbins, MD (2005) Setting the Agenda: Responsible Party Government in the U.S. House of Representatives. New York, NY: Cambridge University Press.CrossRefGoogle Scholar
Crespin, MH (2010) Serving Two Masters: Redistricting and Voting in the US House of Representatives. Political Research Quarterly 63(4): 850–859.CrossRefGoogle Scholar
Crespin, M and Rohde, DW (2010) Dimensions, Issues, and Bills: Appropriations Voting on the House Floor. The Journal of Politics 72: 976–989.CrossRefGoogle Scholar
Crespin, MH and Rohde, D (2016) Political Institutions and Public Choice Roll-Call Database, http://cacexplore.org/pipcvotes/ (accessed 30 March 2017).Google Scholar
Curry, JM and Lee, FE (2019) Non-Party Government: Bipartisan Lawmaking and Party Power in Congress. Perspectives on Politics 17(1): 47–65.CrossRefGoogle Scholar
Dougherty, KL, Lynch, MS and Madonna, AJ (2014) Partisan Agenda Control and the Dimensionality of Congress. American Politics Research 42(4): 600–627.CrossRefGoogle Scholar
Egar, WT (2016) Tarnishing Opponents, Polarizing Congress: The House Minority Party and the Construction of the Roll-Call Record. Legislative Studies Quarterly 41(4): 935–964.CrossRefGoogle Scholar
Ellis, C and Stimson, JA (2012) Ideology in America. New York, NY: Cambridge University Press.CrossRefGoogle Scholar
Ensley, MJ, Tofias, MW and De Marchi, S (2009) District Complexity as an Advantage in Congressional Elections. American Journal of Political Science 53(4): 990–1005.CrossRefGoogle Scholar
Evans, D (2004) Greasing the Wheels: Using Pork Barrel Projects to Build Majority Coalitions in Congress. New York, NY: Cambridge University Press.CrossRefGoogle Scholar
Gerrish, S and Blei, DM (2011) Predicting legislative roll calls from text. In Proceedings of the 28th international conference on machine learning (icml-11): 489–496.Google Scholar
Grimmer, J (2013) Representational Style in Congress: What Legislators Say and Why It Matters. New York, NY: Cambridge University Press.CrossRefGoogle Scholar
Harbridge, L (2015) Is Bipartisanship Dead? Policy Agreement and Agenda-setting in the House of Representatives. New York, NY: Cambridge University Press.CrossRefGoogle Scholar
Jochim, AE and Jones, BD (2013) Issue Politics in a Polarized Congress. Political Research Quarterly 66(2): 352–369.CrossRefGoogle Scholar
Kim, IS, Londregan, J and Ratkovic, M (2018) Estimating Spatial Preferences from Votes and Text. Political Analysis 26(2): 210–229.CrossRefGoogle Scholar
Kingdon, JW (1989) Congressmen’s Voting Decisions. Ann Arbor, MI: University of Michigan Press.CrossRefGoogle Scholar
Krehbiel, K (1991) Information and Legislative Organization. Ann Arbor: University of Michigan Press.CrossRefGoogle Scholar
Krehbiel, K (1998) Pivotal Politics: A Theory of U.S. Lawmaking. Chicago, IL: University of Chicago Press.CrossRefGoogle Scholar
Lee, FE (2009) Beyond Ideology: Politics, Principles, and Partisanship in the U.S. Senate. Chicago, IL: The University of Chicago Press.CrossRefGoogle Scholar
Miller, WE, Stokes, DE (1963) Constituency Influence in Congress. American Political Science Review 57: 45–56.CrossRefGoogle Scholar
Poole, KT (2007) Changing Minds? Not in Congress! Public Choice 131: 435–451.CrossRefGoogle Scholar
Poole, KT and Rosenthal, H (1991) Patterns of Congressional Voting. American Journal of Political Science 35: 228–78.CrossRefGoogle Scholar
Poole, KT and Rosenthal, H (1997) Congress: A Political-Economic History of Roll Call Voting. New York: Oxford University Press.Google Scholar
Poole, KT and Rosenthal, H (2001) D-Nominate after 10 years: A Comparative Update to Congress: A Political-Economic History of Roll-Call Voting. Legislative Studies Quarterly 5–29.CrossRefGoogle Scholar
Poole, KT and Rosenthal, H (2007) Ideology and Congress. New Brunswick, NJ: Transaction Publishers.Google Scholar
Roberts, JM and Smith, SS (2003) Procedural Contexts, Party Strategy, and Conditional Party Voting in the US House of Representatives, 1971–2000. American Journal of Political Science 47(2): 305–317.CrossRefGoogle Scholar
Roberts, ME, Stewart, BM and Tingley, D (2016) Navigating the local modes of big data: The case of topic models.Google Scholar
Roberts, ME, Stewart, BM, Tingley, D and Airoldi, EM (2013) The structural topic model and applied social science. Advances in Neural Information Processing Systems Workshop on Topic Models: Computation, Application, and Evaluation 1–20.Google Scholar
Rohde, DW (1991) Parties and Leaders in the Postreform House. Chicago, IL: University of Chicago Press.CrossRefGoogle Scholar
Rothenberg, LS and Sanders, MS (2000) Severing the Electoral Connection: Shirking in the Contemporary Congress. American Journal of Political Science 44: 316–325.CrossRefGoogle Scholar
Shepsle, KA (1979) Institutional Arrangements and Equilibrium in Multidimensional Voting Models. American Journal of Political Science 23(1): 27–59.CrossRefGoogle Scholar
Smith, SS (2007) Party Influence in Congress. New York, NY: Cambridge University Press.CrossRefGoogle Scholar
Theriault, SM (2008) Party Polarization in Congress. New York, NY: Cambridge University Press.CrossRefGoogle Scholar
Wang, E, Salazar, E, Dunson, D and Carin, L (2013) Spatio-temporal Modeling of Legislation and Votes. Bayesian Analysis 8(1): 233–268.CrossRefGoogle Scholar
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