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Agenda Constrained Legislator Ideal Points and the Spatial Voting Model

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  • Clinton, Joshua D.
  • Meirowitz, Adam

Abstract

Existing preference estimation procedures do not incorporate the full structure of the spatial model of voting, as they fail to use the sequential nature of the agenda. In the maximum likelihood framework, the consequences of this omission may be far-reaching. First, information useful for the identification of the model is neglected. Specifically, information that identifies the proposal locations is ignored. Second, the dimensionality of the policy space may be incorrectly estimated. Third, preference and proposal location estimates are incorrect and difficult to interpret in terms of the spatial model. We also show that the Bayesian simulation approach to ideal point estimation (Clinton et al. 2000; Jackman 2000) may be improved through the use of information about the legislative agenda. This point is illustrated by comparing several preference estimators of the first U.S. House (1789–1791).

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  • Clinton, Joshua D. & Meirowitz, Adam, 2001. "Agenda Constrained Legislator Ideal Points and the Spatial Voting Model," Political Analysis, Cambridge University Press, vol. 9(3), pages 242-259, January.
    • Handle: RePEc:cup:polals:v:9:y:2001:i:03:p:242-259_00
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    Cited by:

    1. Sanford C. Gordon & Dimitri Landa, 2018. "Polarized preferences versus polarizing policies," Public Choice, Springer, vol. 176(1), pages 193-210, July.
    2. Amy McKay, 2008. "A simple way of estimating interest group ideology," Public Choice, Springer, vol. 136(1), pages 69-86, July.
    3. ,, 2010. "Rationalizable voting," Theoretical Economics, Econometric Society, vol. 5(1), January.
    4. Jeong-Hun Han, 2007. "Analysing Roll Calls of the European Parliament," European Union Politics, , vol. 8(4), pages 479-507, December.
    5. Christopher Hare & Keith T. Poole, 2015. "Measuring ideology in Congress," Chapters, in: Jac C. Heckelman & Nicholas R. Miller (ed.), Handbook of Social Choice and Voting, chapter 18, pages 327-346, Edward Elgar Publishing.
    6. Ryan J. Vander Wielen & Michael J. Vander Wielen, 2020. "Unpacking the unknown: a method for identifying status quo distributions," Public Choice, Springer, vol. 182(1), pages 49-72, January.
    7. Tasos Kalandrakis, 2006. "Roll Call Data and Ideal Points," Wallis Working Papers WP42, University of Rochester - Wallis Institute of Political Economy.
    8. Matteo Triossi & Patricio Valdivieso & Benjamín Villena-Roldán, 2013. "A Spatial Model of Voting with Endogenous Proposals: Theory and Evidence from Chilean Senate," Documentos de Trabajo 294, Centro de Economía Aplicada, Universidad de Chile.
    9. Michael A. Bailey & Erik Voeten, 2018. "A two-dimensional analysis of seventy years of United Nations voting," Public Choice, Springer, vol. 176(1), pages 33-55, July.

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