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Unpredictable Voters in Ideal Point Estimation

  • Benjamin E. Lauderdale (a1)
Abstract

Ideal point estimators are typically based on an assumption that all legislators are equally responsive to modeled dimensions of legislative disagreement; however, particularistic constituency interests and idiosyncrasies of individual legislators introduce variation in the degree to which legislators cast votes predictably. I introduce a Bayesian heteroskedastic ideal point estimator and demonstrate by Monte Carlo simulation that it outperforms standard homoskedastic estimators at recovering the relative positions of legislators. In addition to providing a refinement of ideal point estimates, the heteroskedastic estimator recovers legislator-specific error variance parameters that describe the extent to which each legislator's voting behavior is not conditioned on the primary axes of disagreement in the legislature. Through applications to the roll call histories of the U.S. Congress, the E.U. Parliament, and the U.N. General Assembly, I demonstrate how to use the heteroskedastic estimator to study substantive questions related to legislative incentives for low-dimensional voting behavior as well as diagnose unmodeled dimensions and nonconstant ideal points.

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e-mail: blauderd@princeton.edu (corresponding author)
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Author's note: The author thanks Chris Achen, Scott Ashworth, Michael Bailey, Larry Bartels, Charles Cameron, Brandice Canes-Wrone, Joshua Clinton, Kosuke Imai, John Londregan, Nolan McCarty, Adam Meirowitz, Kevin Quinn, Aaron Strauss, and several anonymous reviewers for their comments and suggestions.

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This list contains references from the content that can be linked to their source. For a full set of references and notes please see the PDF or HTML where available.

R. Michael Alvarez , and John Brehm . 1995. American ambivalence towards abortion policy: Development of a heteroskedastic probit model of competing values. American Journal of Political Science 39(4): 1055–82.

Joseph Bafumi , Andrew Gelman , David K. Park , and Noah Kaplan . 2005. Practical issues in implementing and understanding Bayesian ideal point estimation. Political Analysis 13(2): 171–87.

Joshua D. Clinton , Simon Jackman , and Douglas Rivers . 2004a. The statistical analysis of roll call data. American Political Science Review 98(2): 355–70.

Shelby J. Haberman 1977. Maximum likelihood estimates in exponential response models. The Annals of Statistics 5(5): 815–41.

James J. Heckman , and James M. Snyder 1997. Linear probability models of the demand for attributes with an empirical application to estimating the preferences of legislators. RAND Journal of Economics 28(0): S14289.

Simon Hix , Abdul Noury , and Gerard Roland . 2006. Dimensions of politics in the European parliament. American Journal of Political Science 50(2): 494511.

Simon Hix , Abdul Noury , and Gerard Roland . 2007. Democratic politics in the European parliament. New York: Cambridge University Press.

Ralph K. Huitt 1961. The outsider in the senate: An alternative role. American Political Science Review 55(3): 566–75.

Simon Jackman . 2001. Multidimensional analysis of roll call data via Bayesian simulation: Identification, estimation, inference and model checking. Political Analysis 9(3): 227–41.

Samuel A. Kirkpatrick , and Lelan McLemore . 1977. Perceptual and affective components of legislative norms: A social-psychological analysis of congruity. Journal of Politics 39(3): 685711.

John Londregan . 2000. Estimating legislators’ preferred points. Political Analysis 8(1): 3556.

Andrew D. Martin , and Kevin M. Quinn 2002. Dynamic ideal point estimation via Markov chain Monte Carlo for the U.S. Supreme Court, 1953–1999. Political Analysis 10: 134–53.

Nolan McCarty , Keith T. Poole , and Howard Rosenthal . 2001. The hunt for party discipline in congress. American Political Science Review 95: 673–87.

Samuel C. Patterson 1961. The role of the deviant in the state legislative system: The Wisconsin assembly. The Western Political Quarterly 14(2): 460–72.

Keith T. Poole 2000. Nonparametric unfolding of binary choice data. Political Analysis 8(2): 211–37.

Keith T. Poole 2001. The geometry of multidimensional quadratic utility in models of parliamentary roll call voting. Political Analysis 9(3): 211–26.

Keith T. Poole 2005. Spatial models of parliamentary voting. New York: Cambridge University Press.

Keith T. Poole , and Howard Rosenthal . 1985. A spatial model for legislative roll call analysis. American Journal of Political Science 29(2): 357–84.

Erik Voeten . 2000. Clashes in the assembly. International Organization 54(2): 185215.

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Political Analysis
  • ISSN: 1047-1987
  • EISSN: 1476-4989
  • URL: /core/journals/political-analysis
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