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Estimating Parliamentary composition through electoral polls

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  • Frederic Udina
  • Pedro Delicado

Abstract

Summary. All electoral systems have an electoral formula that converts proportions of votes into Parliamentary seats. Pre‐electoral polls usually focus on estimating proportions of votes and then apply the electoral formula to give a forecast of Parliamentary composition. We describe the problems that arise from this approach: there will typically be a bias in the forecast. We study the origin of the bias and some methods for evaluating and reducing it. We propose a bootstrap algorithm for computing confidence intervals for the allocation of seats. We show, by Monte Carlo simulation, the performance of the proposed methods using data from Spanish elections in previous years. We also propose graphical methods for visualizing how electoral formulae and Parliamentary forecasts work (or fail).

Suggested Citation

  • Frederic Udina & Pedro Delicado, 2005. "Estimating Parliamentary composition through electoral polls," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(2), pages 387-399, March.
    • Handle: RePEc:bla:jorssa:v:168:y:2005:i:2:p:387-399
    DOI: 10.1111/j.1467-985X.2005.00354.x
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    References listed on IDEAS

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    1. Benoit, Kenneth, 2000. "Which Electoral Formula Is the Most Proportional? A New Look with New Evidence," Political Analysis, Cambridge University Press, vol. 8(4), pages 381-388, July.
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    Cited by:

    1. José Garcia Montalvo & Omiros Papaspiliopoulos & Timothée Stumpf-Fétizon, 2018. "Bayesian forecasting of electoral outcomes with new parties' competition," Economics Working Papers 1624, Department of Economics and Business, Universitat Pompeu Fabra.
    2. José García-Montalvo & Omiros Papaspiliopoulos & Timothée Stumpf-Fétizon, 2018. "Bayesian Forecasting of Electoral Outcomes with new Parties' Competition," Working Papers 1065, Barcelona School of Economics.
    3. Jarosław Flis & Wojciech Słomczyński & Dariusz Stolicki, 2020. "Pot and ladle: a formula for estimating the distribution of seats under the Jefferson–D’Hondt method," Public Choice, Springer, vol. 182(1), pages 201-227, January.
    4. Montalvo, José G. & Papaspiliopoulos, Omiros & Stumpf-Fétizon, Timothée, 2019. "Bayesian forecasting of electoral outcomes with new parties’ competition," European Journal of Political Economy, Elsevier, vol. 59(C), pages 52-70.

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    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior

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