Abstract

Voting in Iowa and New Hampshire is only a few weeks away, but variance in their early estimates suggest that there are storm clouds on the horizon for the pre-election pollsters – and therefore for everyone involved in the polling and survey research business. Based upon a variety of analyses conducted after the 2008 campaign and the problems that pre-election pollsters had in those primaries, we know that the image of the entire industry rests substantially on the performance of the pre-election polls.1 This is due partly to the fact that preelection polls have a peculiar external validation in the actual outcome of the election that most other polls do not have. In addition, the way that the news media report on “the polls” in the aftermath of an estimation error, especially when they systematically get the winner wrong as they did in New Hampshire, lays generic blame on the method and all those who apply it. In 2008, because of an unusual perspective on estimation issues gleaned through the long series of Democratic primary polls in 2008 due to the extended contest between Barack Obama and Hillary Clinton, we learned that the pre-election polls systematically underestimated the winner’s share of the vote.2 While they rarely got the wrong winner, they did underestimate actual vote share by an amount that was typically greater than sampling error would suggest. Why could the same thing happen again in this cycle? The contextual conditions are almost the same as in 2008. Some states again tried to jump the queue established by the Republican National Committee. Iowa and New Hampshire responded by moving up their dates about a month, from February to early January, on the 3rd and 10th respectively. That means candidates will be

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