One of the great joys of this election for nerds like me is following the debate about how to track the election. There are a few competing models available to look through, such as the Princeton Election Consortium, Votamatic, FiveThirtyEight – and even UnSkewed Polls.
Each of these modelers has taken a different approach to a difficult problem – namely how to estimate the outcome of an election using available data. There are tradeoffs around each approach and there’s a fairly lively debate about which approach is most enlightening. I am excited to see how they fare tomorrow.
On the other hand, you have a bunch of contributors making proclamations about what will happen, seemingly untethered to the evidence available to them. They only show the results of their internal model (should there be one), not the model itself. Obviously many of them are motivated by something other than the “search for truth”, but even if they were, their contribution is generally useless. Here’s why.
First, a model can be useful even if its predictions are wrong. Especially when it is predicting things that are compositional in nature (i.e. not single events in and of themselves, but composed of many events). Second, a model can make a correct prediction even when the model itself is wrong.
Most importantly, when two projections disagree, it’s impossible to work out why they disagree unless we know how the models that produced them work in the first place.
This last point is the most important. Without a model, you are treating projection like opinion.
So: come with a model.