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Smarter Ballots pp 131–166Cite as

Palgrave Macmillan

America Re-votes, 2016: Retrospective Simulations with Smarter Ballots

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Part of the book series: Elections, Voting, Technology ((EVT))

Abstract

This chapter reports some original retrospective election simulation (RES) analyses of contests related to the 2016 American presidential elections. Most notably, the 2016 Republican Party primaries in the USA are simulated to show that the hypothetical use of Ranked-Choice Voting (RCV) rather than the actual 1MB input rules could have resulted in dramatically different outcomes in several states that helped to select Donald Trump as the party’s nominee—provided that certain assumptions about hard-to-measure voter preferences are used rather than others. The general theory suggested by previous election simulations in other countries, that 1MB voting constructs a unique electoral advantage for polarizing parties and candidates which crumbles when multi-mark ballots are used, is supported by this analysis.

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Notes

  1. 1.

    For election simulations in the UK: Steed (1974, 328) and Abramson et al. (2013). For France: Baujard and Igersheim (2010, 2011), Farvaque et al. (2011), Baujard et al. (2014), and Igersheim et al. (2016). For Canada: Blais et al. (2012). For Germany: Alos-Ferrer and Granic (2012) and Granic (2017).

  2. 2.

    Balinski and Laraki (2016).

  3. 3.

    Balinski and Laraki (2010, 5, 8, 134).

  4. 4.

    On Borda Count and manipulative voting: Bassi (2015).

  5. 5.

    Because the January ANES survey was conducted on the World Wide Web, and the respondents were not representative of the population of American adults, I computed means and medians with the weighting variables provided in the ANES data file to get more representative results.

  6. 6.

    For official voting results from the Republican primaries: Berg-Andersson (2017).

  7. 7.

    Quotation at Baujard et al. (2014, 133–34).

  8. 8.

    On feeling thermometers: Abramowitz and McCoy (2019, 148). Quotation at Jacobson (2016, 235).

  9. 9.

    On Le Pen supporters: Blais et al. (2015, 433). On the British Tories: Renwick (2017, 343).

  10. 10.

    Tolbert and Gracey (2018, 81–82). The assessment of methodological challenges in the simulation is my own, not the authors’.

  11. 11.

    Blais et al. (2012, 831).

  12. 12.

    Olsen and Scala (2016, 3–7); I have modified the authors’ original labels for the four factions, which were (respectively) “moderate and liberal,” “somewhat conservative,” “very conservative and religious,” and “very conservative and secular”.

  13. 13.

    Olsen and Scala (2016, 33–121).

  14. 14.

    Olsen and Scala (2016, 134–37, 142).

  15. 15.

    On support for Trump in January: Pew (2016d, 7). For March data: Pew (2016a, 47, 50, 72; 2016d, 13) .

  16. 16.

    Pew Research Center (2016c).

  17. 17.

    On the frequency of leapfrog results in ranking-ballot (RCV and STV) elections: Baldini and Pappalardo (2009, 55).

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  1. University of Louisiana, Lafayette, USA

    J. S. Maloy

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Maloy, J.S. (2019). America Re-votes, 2016: Retrospective Simulations with Smarter Ballots. In: Smarter Ballots. Elections, Voting, Technology. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-13031-2_6

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