Pollster problems in the 2016 US presidential election: vote intention, vote prediction
From Firenze University Press Journal: Italian Journal of Electoral Studies (IJES)
Natalie Jackson, Public Religion Research Institute, Washington, DC, USA
Michael S. Lewis-Beck, Department of Political Science, University of Iowa, USA
Charles Tien, Department of Political Science, Hunter College & The Graduate Center, CUNY, USA
To understand voter choice in American presidential elections, we have come to rely heavily on public opinion surveys, whose questions help explain the electoral outcome. In recent elections, horserace polls — those which measure vote intention, the declaration that you will vote for the Democrat or the Republican, or perhaps a third party — have been explicitly used to predict the outcome of the election in advance in media fore-cast models, exacerbating the reliance on them for election prognostication.
In 2016, national and state-level polls suggested rather strongly that Hillary Clinton would defeat Donald Trump to become the next president of the United States. When it became clear that Trump would instead win the Electoral College, a debate sparked:
Why were such forecasts, based on a mountain of polls, incorrect?
Was this a fundamental failure of polling, or an irresponsible over-reliance on them by forecasters and the media-pundit-ry complex?
Either way, since the media forecasts rely mostly on polls, any widespread polling error should generate considerable concern.
How serious were these apparent errors?
Here we review the performance of the 2016 vote intention polls for president, looking at the national level, where polls performed reasonably well, before turning to the states where the 2016 errors seem particularly grave.
We offer a theoretical explanation for this error rather than the commonly-cited sources of polling error, which focus on poll mode or bias. Our contention is that pre-election polls suffer from a more critical problem: they are trying to poll a population — voters in an upcoming election — which does not exist at the time of the poll.
This assertion means that the polls are not representative of the population they are interpreted to measure even under the best circumstances, making it unsurprising that they sometimes fail spectacularly as prediction tools. Many pollsters have made this exact argument: Polls are a snapshot of what could happen at the time they are taken.
We extend it further by adding the theoretical underpinnings of how polls fail to satisfy representative sample requirements. We offer theoretical and practical support for this hypothesis and argue that because of the inability to sample from the population of actual voters, and the inability to quantify the error that stems from that problem, polls should not be relied upon as prediction tools.
In fact, there is evidence that this type of prediction can be harmful to natural election processes by impacting turn-out. By way of conclusion, we suggest prediction alternatives, turning the focus to modelling the Electoral College result with aggregate (national and state) structural forecasting models and survey-based citizen forecasting.
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