Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-26T20:50:09.917Z Has data issue: false hasContentIssue false

Polarization and Ideology: Partisan Sources of Low Dimensionality in Scaled Roll Call Analyses

Published online by Cambridge University Press:  04 January 2017

John H. Aldrich
Affiliation:
Department of Political Science, Duke University. e-mail: [email protected]
Jacob M. Montgomery*
Affiliation:
Department of Political Science, Washington University in St. Louis, Campus Box 1063, One Brookings Drive, St. Louis, MO 63130-4899
David B. Sparks
Affiliation:
Department of Political Science, Duke University. e-mail: [email protected]
*
e-mail: [email protected] (corresponding author)

Abstract

In this article, we challenge the conclusion that the preferences of members of Congress are best represented as existing in a low-dimensional space. We conduct Monte Carlo simulations altering assumptions regarding the dimensionality and distribution of member preferences and scale the resulting roll call matrices. Our simulations show that party polarization generates misleading evidence in favor of low dimensionality. This suggests that the increasing levels of party polarization in recent Congresses may have produced false evidence in favor of a low-dimensional policy space. However, we show that focusing more narrowly on each party caucus in isolation can help researchers discern the true dimensionality of the policy space in the context of significant party polarization. We re-examine the historical roll call record and find evidence suggesting that the low dimensionality of the contemporary Congress may reflect party polarization rather than changes in the dimensionality of policy conflict.

Type
Research Article
Copyright
Copyright © The Author 2014. Published by Oxford University Press on behalf of the Society for Political Methodology 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

Authors' note: A previous version of this article was presented at the 2009 Annual Meeting of the Southern Political Science Association in Atlanta, GA, and the 2010 Annual Meeting of the American Political Science Association in Washington, DC. We are grateful for comments from Jeff Gill, Frances Lee, Gary Miller, Brendan Nyhan, John Patty, Jon Rogowski, and helpful audiences at Duke University and Washington University in St. Louis. Finally, we thank Keith Poole and Howard Rosenthal for making their roll call data publicly available. Supplementary materials for this article are available on the Political Analysis Web site.

References

Adams, Greg D. 1997. Abortion: Evidence of an issue evolution. American Journal of Political Science 41(3): 718–37.Google Scholar
Aldrich, John H., Montgomery, Jacob M., and Sparks, David. 2010. Drawing (inferences) outside the lines: Dimensionality in Congress. Paper presented at the Annual Meeting of the American Political Science Association.Google Scholar
Aldrich, John H., Montgomery, Jacob M., and Sparks, David B. 2013. Replication data for: Polarization and ideology: partisan sources of low-dimensionality in scaled roll-call analyses. http://dx.doi.org/10.7910/DVN/23248. IQSS Dataverse Network [Distributor] V1 [Version].Google Scholar
Aldrich, John H., and Coleman Battista, James S. 2000. Conditional party government in the States. American Journal of Political Science 46(1): 164–72.Google Scholar
Ansolabehere, Stephen D., Snyder, James M., and Stewart, Charles III. 2001. Candidate positioning in U.S. House elections. American Journal of Political Science 45(1): 136–59.CrossRefGoogle Scholar
Austen-Smith, David, and Banks, Jeffrey. 1988. Elections, coalitions, and legislative outcomes. American Political Science Review 82(2): 405–22.Google Scholar
Bafumi, Joseph, Gelman, Andrew, Park, David K., and Kaplan, Noah. 2005. Practical issues in implementing and understanding Bayesian ideal point estimation. Political Analysis 13(2): 171–87.Google Scholar
Bafumi, Joseph, and Herron, Michael C. 2010. Leapfrog representation and extremism: A study of American voters and their members in Congress. American Political Science Review 104(3): 519–42.Google Scholar
Bartholomew, David, Knott, Martin, and Moustaki, Irini. 2011. Latent variable models and factor analysis: A unified approach. Hoboken: John Wiley and Sons.Google Scholar
Black, Duncan. 1948. On the rationale of group decision-making. Journal of Political Economy 56(1): 2334.Google Scholar
Brady, David W., and Volden, Craig. 2006. Revolving gridlock: Politics and policy from Jimmy Carter to George W. Bush. 2nd ed. Boulder, CO: Westview Press.Google Scholar
Brown, Timothy A. 2006. Confirmatory factor analysis for applied research. New York: Guilford Press.Google Scholar
Cameron, Charles M. 2000. Veto bargaining: Presidents and the politics of negative power. Cambridge, UK: Cambridge University Press.Google Scholar
Carmines, Edward G., and Stimson, James A. 1989. Issue evolution: Race and the transformation of American politics. Princeton, NJ: Princeton University Press.Google Scholar
Carroll, Royce, Lewis, Jeffrey B., Lo, James, Poole, Keith, and Rosenthal, Howard. 2009. Comparing NOMINANT and IDEAL: Points of difference and Monte Carlo tests. Legislative Studies Quarterly 34(4): 555–91.Google Scholar
Cattell, Raymond B. 1966. The Scree test for the number of factors. Multivariate Behavioral Research 1(2): 245–76.Google Scholar
Clausen, Aage. 1973. How congressmen decide: A policy focus. New York: St. Martin's Press.Google Scholar
Clinton, Josh D., and Meirowitz, Aadam. 2001. Agenda constrained legislator ideal points and the spatial voting model. Political Analysis 9(3): 242–59.Google Scholar
Clinton, Joshua D. 2007. Lawmaking and roll calls. Journal of Politics 69(2): 457–69.Google Scholar
Clinton, Joshua D. 2012. Using roll call estimates to test models of politics. Annual Review of Political Science 15: 7999.Google Scholar
Clinton, Joshua D., and Jackman, Simon. 2009. To simulate or NOMINATE? Legislative Studies Quarterly 34: 593621.Google Scholar
Clinton, Joshua, Jackman, Simon, and Rivers, Douglas. 2004. The statistical analysis of roll call data. American Political Science Review 98(2): 355–70.Google Scholar
Cox, Gary W., and Poole, Keith T. 2002. On measuring partisanship in roll call voting: The US House of Representatives, 1877–1999. American Journal of Political Science 46(3): 477–89.CrossRefGoogle Scholar
Cox, Gary W., and McCubbins, Matthew D. 2005. Setting the agenda: Responsible party government in the US House of Representatives. New York: Cambridge University Press.Google Scholar
Crespin, Michael, and Rohde, David W. 2010. Dimensions, issues, and bills: Appropriations voting on the House floor. Journal of Politics 72(4): 976–89.Google Scholar
Dougherty, Keith L., Lynch, Michael S., and Modonna, Anthony. 2012. Partisan agenda control and the dimensionality of congress. Unpublished manuscript.Google Scholar
Downs, Anthony. 1957. An economic theory of democracy. New York: Harper and Row.Google Scholar
Enelow, James M., and Hinich, Melvin. 1984. The spatial theory of voting. New York: Cambridge University Press.Google Scholar
Erosheva, Elena A., and McKay Curtis, S. 2011. Dealing with rotational invariance in Bayesian confirmatory factor analysis. Technical Report 589, University of Washington. http://www.stat.washington.edu/research/reports/2011/tr589.pdf.Google Scholar
Ghosh, Joyee, and Dunson, David B. 2009. Default prior distributions and efficient posterior computation in Bayesian factor analysis. Journal of Computational and Graphical Statistics 18(2): 306–20.Google Scholar
Gilligan, Thomas W., and Krehbiel, Keith. 1989. Asymmetric information and legislative rules with a heterogeneous committee. American Journal of Political Science 33(2): 459–90.Google Scholar
Heckman, James J., and Snyder, James M. Jr. 1997. Linear probability models of the demand for attributes with an empirical application to estimating the preferences of legislators. RAND Journal of Economics 28: 142–89.Google Scholar
Herron, Michael C. 2004. Studying dynamics in legislator ideal points: Scale matters. Political Analysis 12(2): 182–90.Google Scholar
Hinich, Melvin J., and Munger, Michael C. 1994. Ideology and the theory of political choice. Ann Arbor: University of Michigan Press.Google Scholar
Hirsch, Alexander V. 2011. Theory driven bias in ideal point estimates—A Monte Carlo study. Political Analysis 19(1): 87102.Google Scholar
Horn, John L. 1965. A rationale and test for the number of factors in factor analysis. Psychometrika 30(2): 179–85.Google Scholar
Hurwitz, Mark S., Moiles, Roger J., and Rohde, David W. 2001. Distributive and partisan issues in agriculture policy in the 104th House. American Political Science Review 95(4): 911–22.Google Scholar
Iversen, Torben, and Soskice, David. 2001. An asset theory of social policy preferences. American Political Science Review 95(4): 875–93.Google Scholar
Jackman, Simon. 2001. Multidimensional analysis of roll call data via Bayesian simulation: Identification, estimation, inference, and model checking. Political Analysis 9(3): 227–41.Google Scholar
Jenkins, Jeffery A. 1999. Examining the bonding effects of party: A comparative analysis of roll-call voting in the U.S. and Confederate Houses. American Journal of Political Science 43(4): 1144–65.Google Scholar
Jenkins, Jeffery A. 2000. Examining the robustness of ideological voting: Evidence from the Confederate House of Representatives. American Journal of Political Science 44(4): 811–22.Google Scholar
Jessee, Stephen A. 2009. Spatial voting in the 2004 presidential election. American Political Science Review 103(1): 5981.Google Scholar
Jessee, Stephen A. 2010. Partisan bias, political information and spatial voting in the 2008 presidential election. Journal of Politics 72(2): 327–40.Google Scholar
Kaiser, Henry F. 1960. The application of electronic computers to factor analysis. Educational and Psychological Measurement 20(1): 141.Google Scholar
Karol, David. 2009. Party position change in American politics: Coalition management. New York: Cambridge University Press.Google Scholar
Kramer, Gerald H. 1973. On a class of equilibrium conditions for majority rule. Econometrica 41(2): 285–97.Google Scholar
Krehbiel, Keith. 1992. Information and legislative organization. Ann Arbor: University of Michigan Press.Google Scholar
Krehbiel, Keith. 1998. Pivotal politics: A theory of U.S. lawmaking. Chicago: University of Chicago Press.Google Scholar
Laver, Michael, and Shepsle, Kenneth A. 1990. Coalitions and cabinet government. American Political Science Review 84(3): 873–90.Google Scholar
Layman, Geoffrey C., and Carsey, Thomas M. 2002. Party polarization and “conflict extension” in the American electorate. American Journal of Political Science 46(4): 786802.CrossRefGoogle Scholar
Lee, Frances E. 2009. Beyond ideology: Politics, principles, and partisanship in the U.S. Senate. Chicago: University of Chicago Press.Google Scholar
MacRae, Duncan. 1958. Dimensions of congressional voting: A statistical study of the House of Representatives in the Eighty-First Congress. Berkeley: University of California Press.Google Scholar
Martin, Andrew D., and Quinn, Kevin M. 2002. Dynamic ideal point estimation via Markov chain Monte Carlo for the U.S. Supreme Court, 1953–1999. Political Analysis 10(2): 134–53.Google Scholar
Masket, Seth E. 2007. It takes an outsider: Extralegislative organization and partisanship in the California Assembly, 1849–2006. American Journal of Political Science 51(3): 482–97.Google Scholar
Norton, Noelle H. 1999. Uncovering the dimensionality of gender voting in Congress. Legislative Studies Quarterly 24(1): 6586.Google Scholar
Palfrey, Thomas R. 1989. A mathematical proof of Duverger's law. In Models of strategic choice in politics, ed. Ordershook, Peter C., 6991. Ann Arbor: University of Michigan Press.Google Scholar
Patty, John W. 2008. Equilibrium party government. American Journal of Political Science 52(3): 636–55.Google Scholar
Peltzman, Sam. 1985. An economic interpretation of the history of congressional voting in the twentieth century. American Economic Review 75(4): 656–57.Google Scholar
Persson, Torsten, and Tabellini, Guido. 2000. Political economics: Explaining economic policy. Boston, MA: MIT Press.Google Scholar
Poole, Keith T. 2005. Spatial models of parliamentary voting. New York: Cambridge University Press.Google Scholar
Poole, Keith T., Sowell, Fallaw B., and Spear, Stephen E. 1992. Evaluating dimensionality in spatial voting models. Mathematical and Computer Modeling 16 (8–9): 85101.Google Scholar
Poole, Keith T., and Rosenthal, Howard. 1991. Patterns of congressional voting. American Journal of Political Science 35: 228–77.Google Scholar
Poole, Keith T., and Rosenthal, Howard. 1997. Congress: A political-economic history of roll call voting. New York: Oxford University Press.Google Scholar
Poole, Keith T., and Rosenthal, Howard. 2007. Ideology & Congress. New Brunswick, NJ: Transaction Publishers.Google Scholar
Poole, Keith T., Lewis, Jeffrey B., Lo, James, and Carroll, Royce. 2011. Scaling roll call votes with WNOMINATE in R. Journal of Statistical Software 42(14): 121.Google Scholar
Roberts, Jason M. 2007. The statistical analysis of roll-call data: A cautionary tale. Legislative Studies Quarterly 32(3): 341.Google Scholar
Roberts, Jason M., and Smith, Steven S. 2003. Procedural contexts, party strategy, and conditional party voting in the U.S. House of Representatives, 1971–2000. American Journal of Political Science 47(2): 305–17.Google Scholar
Roberts, Jason M., Smith, Steven S., and Haptonstahl, Stephen R. 2009. The dimensionality of congressional voting reconsidered. Paper presented at the Duke University Conference on Bicameralism.Google Scholar
Romer, Thomas, and Rosenthal, Howard. 1978. Political resource allocation, controlled agendas, and the status quo. Public Choice 33(4): 2743.Google Scholar
Schattschneider, E. E. 1960. The semi-sovereign people: A realist's view of democracy in America. New York: Holt, Rinehart, and Winston.Google Scholar
Shepsle, Kenneth A., and Weingast, Barry R. 1987. Institutional foundations of committee power. American Political Science Review 81(1): 85104.Google Scholar
Shepsle, Kenneth A., and Weingast, Barry R. 1994. Positive theories of congressional institutions. Legislative Studies Quarterly 19(2): 149–79.Google Scholar
Snyder, James M. 1992a. Committee power, structure-induced equilibria, and roll call votes. American Journal of Political Science 36(1): 130.Google Scholar
Snyder, James M. 1992b. Gatekeeping or not, sample selection in the roll call agenda matters. American Journal of Political Science 36(1): 3639.Google Scholar
Snyder, James M., and Groseclose, Tim. 2000. Estimating party influence in congressional roll-call voting. American Journal of Political Science 44(2): 193211.Google Scholar
Stiglitz, Edward H., and Weingast, Barry R. 2010. Agenda control in Congress: Evidence from cutpoint estimates and ideal point uncertainty. Legislative Studies Quarterly 35(2): 157–85.CrossRefGoogle Scholar
Talbert, Jeffrey C., and Potoski, Matthew. 2002. Setting the legislative agenda: The dimensional structure of bill cosponsoring and floor voting. Journal of Politics 64(03): 864–91.Google Scholar
Welch, Susan, and Carlson, Eric H. 1973. The impact of party on voting behavior in a nonpartisan legislature. American Political Science Review 67(3): 854–67.Google Scholar
Wilcox, Clyde, and Clausen, Aage. 1991. The dimensionality of roll-call voting reconsidered. Legislative Studies Quarterly 16(3): 393406.Google Scholar
Wright, Gerald C., and Schaffner, Brian F. 2002. The influence of party: Evidence from the state legislatures. American Political Science Review 96(2): 367–79.Google Scholar
Supplementary material: PDF

Aldrich et al. supplementary material

Supplementary Material

Download Aldrich et al. supplementary material(PDF)
PDF 607.5 KB