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Forecasting runoff elections using candidate evaluations from first round exit polls

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  • Selb, Peter
  • Herrmann, Michael
  • Munzert, Simon
  • Schübel, Thomas
  • Shikano, Susumu

Abstract

We draw attention to a simple yet underappreciated way of forecasting the outcomes of elections involving two rounds of voting: surveying the voters’ candidate evaluations in first round exit polls, poststratifying the sample proportions of reported votes to official first round election returns, and redistributing the votes for eliminated competitors according to their supporters’ lower-order preferences among the viable alternatives in round two. We argue that the approach is likely to outperform standard pre-election surveys, due to its better coverage and reduced measurement error, and the possibility of correcting for sample selection. We set out the practical details of the method and demonstrate its usefulness by employing a recent German mayoral election as an empirical case. Thirteen candidates were competing in the first round, while there were six candidates in the decisive second round. The runoff result was forecast two weeks in advance with an average absolute error of less than one percentage point.

Suggested Citation

  • Selb, Peter & Herrmann, Michael & Munzert, Simon & Schübel, Thomas & Shikano, Susumu, 2013. "Forecasting runoff elections using candidate evaluations from first round exit polls," International Journal of Forecasting, Elsevier, vol. 29(4), pages 541-547.
  • Handle: RePEc:eee:intfor:v:29:y:2013:i:4:p:541-547
    DOI: 10.1016/j.ijforecast.2013.02.001
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    References listed on IDEAS

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    1. Weisberg, Herbert F. & Rusk, Jerrold G., 1970. "Dimensions of Candidate Evaluation," American Political Science Review, Cambridge University Press, vol. 64(4), pages 1167-1185, December.
    2. Brady, Henry E. & Ansolabehere, Stephen, 1989. "The Nature of Utility Functions in Mass Publics," American Political Science Review, Cambridge University Press, vol. 83(1), pages 143-163, March.
    3. Justin Wolfers & Eric Zitzewitz, 2004. "Prediction Markets," Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 107-126, Spring.
    4. Sakurai, Sergio N. & Menezes, Naercio A., 2008. "Fiscal policy and reelection in Brazilian municipalities," Insper Working Papers wpe_117, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    5. Jerome, Bruno & Jerome, Veronique & Lewis-Beck, Michael S., 1999. "Polls fail in France: forecasts of the 1997 legislative election1," International Journal of Forecasting, Elsevier, vol. 15(2), pages 163-174, April.
    6. repec:reg:rpubli:259 is not listed on IDEAS
    7. Plutzer, Eric, 2002. "Becoming a Habitual Voter: Inertia, Resources, and Growth in Young Adulthood," American Political Science Review, Cambridge University Press, vol. 96(1), pages 41-56, March.
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    Cited by:

    1. Antoinette Baujard & Isabelle Lebon, 2022. "Not-so-strategic Voters," Working Papers 2201, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    2. Antoinette Baujard & Isabelle Lebon, 2022. "Not-so-strategic voters. Evidence from an in situ experiment during the 2017 French presidential election [Wp Gate 2022-2201]," Working Papers halshs-03607809, HAL.

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