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Legislative Organization and Ideal-Point Bias

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  • Krehbiel, Keith

    (Stanford University)

  • Peskowitz, Zachary

    (OH State University)

Abstract

Four pure types of legislative organization are characterized as data generating processes for commonly used measures of preferences or, in the spatial vernacular, ideal points. The types of legislative organization are differentiated by their partisan versus nonpartisan nature of agenda formation, and by whether the amendment process is open or closed. For each organization, roll call voting data are Monte-Carlo generated and used as input for four different ideal point measures: standard percent-correct interest group ratings (IGRs), linear factor analysis scores (LFAs), W-NOMINATE ratings (NOMs), and Markov chain Monte Carlo measures (MCMCs). Three questions motivate and are addressed the analysis. Do estimated ideal points differ significantly across forms of legislative organization? Are some ideal point estimates consistently more accurate than others? Are there patterns of substantively relevant, persistent bias in ideal point estimates? The answers are all affirmative.

Suggested Citation

  • Krehbiel, Keith & Peskowitz, Zachary, 2012. "Legislative Organization and Ideal-Point Bias," Research Papers 2124, Stanford University, Graduate School of Business.
    • Handle: RePEc:ecl:stabus:2124
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    References listed on IDEAS

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    1. Binder, Sarah A., 1999. "The Dynamics of Legislative Gridlock, 1947–96," American Political Science Review, Cambridge University Press, vol. 93(3), pages 519-533, September.
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    5. Austen-Smith, David, 1987. "Sophisticated Sincerity: Voting Over Endogenous Agendas," American Political Science Review, Cambridge University Press, vol. 81(4), pages 1323-1330, December.
    6. Hetherington, Marc J., 2001. "Resurgent Mass Partisanship: The Role of Elite Polarization," American Political Science Review, Cambridge University Press, vol. 95(3), pages 619-631, September.
    7. Snyder, James M. & Groseclose, Tim, 2001. "Estimating Party Influence on Roll Call Voting: Regression Coefficients versus Classification Success," American Political Science Review, Cambridge University Press, vol. 95(3), pages 689-698, September.
    8. Groseclose, Tim & Levitt, Steven D. & Snyder, James M., 1999. "Comparing Interest Group Scores across Time and Chambers: Adjusted ADA Scores for the U.S. Congress," American Political Science Review, Cambridge University Press, vol. 93(1), pages 33-50, March.
    9. Gilligan, Thomas W & Krehbiel, Keith, 1987. "Collective Decisionmaking and Standing Committees: An Informational Rationale for Restrictive Amendment Procedures," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 3(2), pages 287-335, Fall.
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    Cited by:

    1. Ugur Ozdemir & Ali Ihsan Ozkes, 2014. "Measuring Public Preferential Polarization," Working Papers hal-00954497, HAL.

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