In this post I want to try to answer several of the excellent questions posted in response to some of my earlier blogs.
First, Conor Shaw points out that although my rule of thumb that McCain does better in surveys of likely voters, while Obama does better in polls of registered voters, may hold at the national level, the reverse seems to be the case in the key battleground state of Virginia. Recent polls there show Obama doing better in surveys of likely voters than of registered voters. It is difficult to explain why Virginia is polling differently because it is one of the more than 20 states that does not keep party registration figures. But my guess is that the answer lies in the proportion of Democrats, especially African-Americans, that are being sampled in the likely voter surveys compared to surveys of registered voters. For example, SurveyUSA included 33% Democrats in their latest poll of likely voters compared to 38% Republicans and 22% Independents, and had Obama beating McCain by 6%, 51-45 in Virginia. That may be a higher proportion of Democrats than is included in the polls of registered voters. Similarly, a PPP poll that had Obama up by 4% included 21% African-Americans, but a Newport poll in Virginia that had McCain up by 9% only sampled 10% African Americans. According to exit polls (which may not be completely accurate), African-Americans composed about 22% of the Virginia voters in the 2004 election. Again, this just reinforces my earlier point regarding the need to check the pollsters’ internal weighting for clues to explain different survey outcomes. With registration running high this election cycle, it is often a guessing game to determine just how to weight the different demographic groups. Keep in mind that Bush won Virginia by 262,217 votes in 2004. But as of September 8th of this year, more than 285,000 people have been added to the registration rolls since that election. How many are Democrats? We can’t tell, but the Obama campaign believes that the demographics of the newly registered voters, particular the high number of registrants under age 40, favor him. However, Brian Schaffner at Pollster.com suggests that based on where the registration is taking place, it’s not clear how many of the newly registered voters are in fact likely to vote for Obama, since the majority of the new voters registered in areas that went for Bush in 2004. Keep in mind as well that in a state where more than 3 million people cast votes in 2004, Obama can’t hope to win based on newly registered voters alone; he will need to peel off some of the Bush coalition as well.
Both Bhima and Polemarchus are interested in the track record of the forecast models in previous elections. I will try to present some summary statistics for those models that have been in use for several elections. The questions highlight an interesting problem with some of these models, however: some forecasters tweak their models after the fact to make them appear to “fit” with past elections. In effect, then, rather than test assumptions about what makes voters behave as they do, these forecasters instead adjust the numbers to make it appear retrospectively that the models predicted past elections better than they did at the time. These types of adjustments don’t necessarily reflect an understanding of the forces that account for elections outcomes, so we need to be careful when judging a forecast model based on how well it predicts all past elections.
Polemarchus also raises a point cited by several others: if we can predict elections before the general election campaigns begin, why even bother campaigning? This is not a facetious question. Let’s be clear here: the models don’t assume that campaigns don’t matter. In fact, campaigns do matter in at least two important respects. First, most forecast models assume that both major party campaigns will be effective at framing the voting context in ways that their likely voter coalition will find most appealing. As long as the modelers can measure “reality”, then, they should be able to account for these campaign framing effects. Second, campaigns help mobilize voters. Indeed, one of the big questions that may throw the forecast models off this year is turnout. A huge turnout, particularly among one party’s voting coalition, can undermine the assumptions built into the forecast model. So we need to keep an eye on turnout levels. Here’s the turnout among eligible and registered voters for presidential elections dating back to the 1940′s, pasted from Michael McDonald’s valuable election site: http://elections.gmu.edu/turnout_rates_graph.htm
Note that after an almost uniform decline since 1964, turnout of eligible voters (and of the voting age public) has gone up during the last two elections, topping 60% in 2004. My expectation is that this election will continue that trend, with turnout above the 2004 level. How will that affect the forecast models? I’ll try to address that in a future post.
Keep those questions coming!