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Model-based pre-election polling for national and sub-national outcomes in the US and UK

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  • Lauderdale, Benjamin E.
  • Bailey, Delia
  • Blumenau, Jack
  • Rivers, Douglas

Abstract

We describe a strategy for applying multilevel regression and post-stratification (MRP) methods to pre-election polling. Using a combination of contemporaneous polling, census data, past election polling, past election results, and other sources of information, we are able to construct probabilistic, internally consistent estimates of national votes and the sub-national electoral districts that determine seats or electoral votes in many electoral systems. We report on the performance of the general framework in three applications that were conducted and released publicly in advance of the 2016 UK Referendum on EU Membership, the 2016 US Presidential Election, and the 2017 UK General Election.

Suggested Citation

  • Lauderdale, Benjamin E. & Bailey, Delia & Blumenau, Jack & Rivers, Douglas, 2020. "Model-based pre-election polling for national and sub-national outcomes in the US and UK," International Journal of Forecasting, Elsevier, vol. 36(2), pages 399-413.
    • Handle: RePEc:eee:intfor:v:36:y:2020:i:2:p:399-413
    DOI: 10.1016/j.ijforecast.2019.05.012
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    References listed on IDEAS

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    Cited by:

    1. Hanretty, Chris, 2021. "Forecasting multiparty by-elections using Dirichlet regression," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1666-1676.

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