538: Why Our Model Is Bullish On Trump, For Now
So which one is correct? That’s another tricky question. If you’re using loess regression for descriptive purposes — to illustrate how the polls have moved in the past — the more aggressive trend line is clearly better. It does a much better job of capturing movement in the polls — we had more than enough data to know that Clinton moved up in the polls from May to June, for instance. But if you’re using loess to make predictions — to anticipate where the polls are going to go next — there’s an argument for using a more conservative setting. That’s because short-term movement in the polls often reverses itself — a candidate gets a bad news cycle, and she drops a couple of percentage points, but she recovers them once the news moves along to another subject. The convention bounce is one example of this, in fact, since the bounces often reverse themselves after a few weeks.
We spent a lot of time on this issue when originally building our model in 2008 and then when revising it in 2012 and earlier this year, trying to figure out how aggressive these loess curves should be in order to maximize predictive accuracy. The short answer is that you want an aggressive setting — very aggressive, in fact — late in the campaign, and a more conservative one earlier on.1 Still, it’s certainly also possible to be too conservative, which could mean missing the considerable shift away from Clinton that began a few weeks ago in the polls, well ahead of the conventions.
Another tricky question is how to reconcile state polls with national polls. For example, there have been no polls of Pennsylvania over the past two weeks, during which time Clinton’s lead has evaporated in national polls (and often also in polls of other states, where we’ve gotten them). The FiveThirtyEight model uses what we call a trend-line adjustment to adjust those those old polls to catch up to the current trend. That’s why our polls-only forecast shows Pennsylvania as a tossup even though Trump has only led one poll there all year. Those older polls came from a time when Clinton led by 5 or 6 or 7 percentage points nationally, and they generally showed her up by about the same margin in Pennsylvania. Now that the national race is almost tied, it’s probably safe to assume that Pennsylvania is very close also. Some of the competing models don’t do this, and we think that’s probably a mistake, since it means their state-by-state forecasts will lag a few weeks behind, even when it’s obvious there’s been a big shift in the race.
Bottom line: Although there are other factors that matter around the margin, our models show better numbers for Trump mostly because they’re more aggressive about detecting trends in polling data. For the past couple of weeks — and this started before the conventions, so it’s not just a convention bounce — there’s been a strong trend away from Clinton and toward Trump. Although there’s always the risk of overreaction, this time our models were ahead of the curve in understanding the shift. But if Clinton rebounds next month, our models may be among the first to show that as well.
http://fivethirtyeight.com/features/election-update-why-our-model-is-bullish-on-trump-for-now/
