• Is 99% Too High?

    by  • June 27, 2012 • Uncategorized • 9 Comments

    That depends on whether you believe the historical model. Of all the numbers on this site – and there are a lot of them – the one that may be most eye-catching right now is the high probability my model places on Obama’s chances for re-election. Whether that probability is 99%, 95%, or 90% (there will be blips up and down), the point is that the model is very confident in forecasting an Obama victory.

    Is 99% too high? Given the current polling data, and how this year’s fundamentals compare to those of previous presidential elections, I don’t think it is. The baseline forecast I am working from estimates that Obama will win 52.7% of the national (two-party) vote right off the bat. When translated to the state level, combined with current polls, then converted into electoral votes, the median forecast is Obama 328 – Romney 210. There’s actually quite a bit of uncertainty around these estimates, though. The model indicates that with 90% probability, Obama’s electoral vote total could be anywhere from 281 (e.g., Bush vs. Kerry) to 367 (e.g., Clinton vs. Bush). The entire range of simulated Obama electoral votes is roughly 225 to 425. The reason the model is so confident is not because the uncertainty in the estimates is too small, but because the underlying data are tilted so far in Obama’s direction.

    That said, this does not mean that the forecasts are fixed, or that the election is over. The key to my approach is that it is dynamic: when older forecasts conflict with newer polling data, it updates the estimates automatically. At some point in the campaign – whether it’s one week before the election, one month, or even now – the model predictions will be correct (that is, at least, as long as the polls are accurate, which I sure hope they will be). What we won’t know until Election Day is how quickly the model got us to the right answer.

    In fact, the biggest missing piece at the moment is not more polls, but rather the Q2 economic data. By necessity, I’m still relying on Q1 data, even though they are historically less predictive. As soon as the Q2 numbers are released, I will recalculate the baseline structural forecast, and continue updating from there. That’s been the plan all along. (…but if Q2 growth is around 2% – as some expect – the baseline forecast will end right back up at 52-53%.)

    So just as you wouldn’t look at the weather forecast a week ahead, then not re-check the day before, the model is telling us how things look right now, subject to new information later on. It’s not impossible for Romney to win, and I’m not guaranteeing an Obama victory. But, barring any major, historically exceptional turn of events, it’s very reasonable to think that Obama has a very, very good chance of winning in 2012.

    9 Responses to Is 99% Too High?

    1. June 28, 2012 at 5:07 am

      You didn’t actually say this above, but it sounds like you’re saying this is an “if the election were held right now” win probability, yes? That’s the only way such a high number can make any sense (and probably not even then). If this is the case, I’m skeptical as to how useful it is, particularly with no other model that takes a longer view.

    2. Drew
      June 28, 2012 at 9:54 am

      Chris, I actually estimate both. The poll tracker shows where things stand today, but the forecasts are meant to be proper forecasts of what will happen on Election Day. The longer-view model for this is based on historical data as I talk about on the “how it works” page. The structural model provides a baseline set of forecasts, which are updated and refined by the current polls.

    3. June 28, 2012 at 10:05 am

      But are the forecasts forward-looking? I mean, I feel like you could pick any election, completely ignore the economic data or the polls, and confidently proclaim in June that no candidate has ever really had a 99% chance of winning, without so much as glancing at any data. I know my objection isn’t very formal, but that’s a staggering claim.

    4. Drew
      June 28, 2012 at 3:02 pm

      Yes, it is forward-looking. I understand why it seems staggering. The forecast is based on a historical model that suggests Obama will only do about 1% worse, on average, than he did in 2008. Think of it this way: what if historical factors suggested Obama would win 58% of the vote, like Reagan’s landslide vs. Mondale? To my mind, if you believe the model, you’d also have to be willing to put a very high probability on him winning.

      The counter to this perspective is as you say — no matter what the structural measures indicate in June or July, there’s just too much noise in the data and uncertainty about what might happen later to be making such strong forecasts. That’s entirely possible, and if I’m wrong, we’ll know soon. A saving grace (I hope) is that since the model is dynamic, the forecasts will improve with more polling data closer to the election. I’m as curious as anyone to see how this unfolds.

    5. June 28, 2012 at 3:13 pm

      If the historical factors suggested Obama would win 58% of the vote, then I guess I’d understand the probability being 99%…but they don’t suggest that, yeah? You say they suggest he will only do about 1% worse, which would be 51.9%. So in order to get to 99%, the model would have to be INCREDIBLY confident that that represented his floor, wouldn’t it?

      Also, when you say historical factors, what do you mean? That incumbents usually only do about 1% worse? I take it this is something a little more complicated than an average, which is going to be made up of three examples of an incumbent doing better and then one where they do significantly worse, just going off my general memory of the history of the Presidency.

      Re: “if I’m wrong, we’ll know soon.” Well, we might. The polling might be just as good for him, but the tricky part about this stuff (as I’m sure you realize) is that we’ll never actually know if your probability in June was dead-on. If Obama loses (or very narrowly wins), we can probably assume it was heavily flawed (because the alternative is that 1% chance coming to pass). But if he wins by any kind of significant margin, we wouldn’t have any way to know whether or not this degree of confidence in June was warranted, or just happened to coincide with the eventual result.

      Cutting through all that, though, do you actually believe it? Would you take 99-1 odds on a bet, for example?

    6. June 28, 2012 at 3:13 pm

      Oh, and I forgot to say: thanks for indulging my questions.

    7. Drew
      June 28, 2012 at 3:37 pm

      It’s 1% less than his share of the major-party vote only, so actually 52.7%, down from 53.7% in 2008. I’ve tried to explain more about this on the how it works page.

      I do agree with you about the difficulty in evaluating early, probabilistic predictions like this, though. My worst-case scenario – from a purely forecasting standpoint! – is that nothing really major or historically weird happens between now and November, yet Romney wins by a fair margin. It could happen.

      For what it’s worth, I did offer a friend 25-1 odds yesterday. So that’s about a 96% win probability. But I told him he could only bet me $1.

    8. Tyson
      July 2, 2012 at 1:36 pm

      Drew, what happened to the probability Obama will win (i.e., the 99%)? I don’t see it prominently displayed anymore. I hope you didn’t lose your nerve. It looks like the confidence intervals have moved apart since you started the site. Are Obama’s chances now estimated at over 99.5%, so you’d have to round it up to 100% without adding digits?

    9. Drew
      July 2, 2012 at 4:06 pm

      Tyson, yes, you noticed. At this point in the campaign, I felt like it was just too distracting up there. Without an explanation of the priors I’m using, I think people were understandably skeptical. I’ll bring it back later this summer once more polling data comes in. In the meantime (as you also noticed), the same information is essentially available from the intervals around the EV forecast and in the EV simulation histogram on the forecast detail page.

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