The Alchemy of Making Election Predictions

Four years can be a long time in politics, and one midterm cycle may not resemble the one immediately preceding it. For a pollster, political scientist, or basement-dwelling blogger, there are tools and practices that can be put to use to assist the gut in making predictions about electoral outcomes. The ones we are most familiar with are efforts to discern patterns in the electorate’s behavior by looking at the broadest relevant data set that can be obtained. Yet, from a scientific point of view, we hold so few elections and our elections (e.g. general vs. midterm vs. local) are so distinct from each other that we never really have a very robust data set. Even with the data we have, there are events that change the nature of the country and that make old election data suspect when used in conjunction with relatively recent election data. Big events like the Vietnam War, Watergate, the Reagan and Gingrich revolutions, the end of the Cold War, 9/11, the second Iraq War, Hurricane Katrina, and the Great Recession combine with slow but persistent demographic change and internal migration, as well as changing election law to change both the composition of the electorate and how it views the world.

We know for example that in the four years since the 2010 midterms some states have undergone some significant changes or experienced some unusual events. California has been suffering from an historic drought. North Dakota has been experiencing a massive oil and gas boom. North Carolina has been governed by a radical Republican Party for the first time since the 19th Century. Pennsylvania has had close to the slowest job growth of any state in the country. Colorado and Washington created a market for the legal sale of marijuana. Georgia has seen a big reverse-migration of African Americans. And many states now have gay marriage which did not in 2010.

Most of these types of developments are not typically considered or captured in the models we make to predict elections, and are usually relegated to the gut if they are considered by analysts at all.

How, after all, could one scientifically predict the political impact of marijuana legalization or gay marriage?

What tends to happen is that we poll people and use the results as our baseline. Then we try to explain those polls. But that’s a problem. It’s a problem right now because the rule is that midterm Senate election polls are biased in one direction or another, usually by at least two points. If you take a look at the Real Clear Politics aggregation of polls, four of the top ten Senate races show a lead of less than two percent and the same is true of eight of the top ten gubernatorial races. If history is a reliable guide, these polls are off by a little bit in one direction or another, meaning that there is a skew in favor of either the Democrats or the Republicans. This is irrespective of the unique or particular factors at play in each state and race.

And those factors can be decisive. It’s going to be harder for Bruce Braley to exceed expectations in Iowa because the incumbent Republican governor at the top of the ticket is going to win by a large margin. It’s going to be harder for Thom Tillis to win in North Carolina because he was the Speaker of the House in a very unpopular state legislature. The hope is that these features of campaigns are somehow captured in the polls, but they may not be, or they may be captured only partially.

Over this weekend, I am going to look at a few Senate races and I am going to try to go a little beyond the polls to make predictions about who will win and why.

Martin Longman

Martin Longman is the web editor for the Washington Monthly and the main blogger at Booman Tribune.