In the months leading up to this election year these pages have recorded a lot of predictions, some more vehement than others. Predicting, estimating, forecasting, …, all of them are hard and involve some level of risk depending how well these efforts are carried out. We spend almost every waking moment taking some kind of peek into the future, and depending on how certain we are of what we see there, we take an action which may involve some kind of hedging if we’re not too confident about what we see.
I’ve always been interested in how well we can prognosticate. Recently nobelist Daniel Kahneman of Kahneman/Tversky fame wrote what instantly became a very famous essay - Thinking Fast and Slow (2011) - on the findings of research into things such as prediction, estimation, risk aversion, reasoning and so on. Bottom line – research to date has shown that humans are mostly not very good predictors, and they don’t always do the reasonable things. Yet we do have a brain bone that has allowed us to survive over the millennia and evolve our thinking capacity to some pretty commendable levels. After all, we did discover relativity, sequence the human genome, put a man on the Moon, and are about to devise an AI that may make us second class citizens on our own planet.
So how well can we predict? Here I propose a fun experiment on the topic that invites RR readers to go on record and compete with each other predicting anything they want and, hopefully, get someone else interested enough to also render their prediction. I offer an easy, intuitive, and enjoyable way to do this using the MAB distribution which asks you to specify four numbers that characterize your prediction. The method is spelled out in a previous post ‘Predicting with Expressed Beliefs – a formal approach’.
Since this is election season, say you want to predict what percent of the Democrat vote Bernie Sanders will get in this Tuesday’s New Hampshire primary. Today that percentage is a random variable, but next Wednesday it will be known and no longer random. All such future values are random variables, and the best we can do to express them is to characterize our belief in the value of the variable is to describe what is called its probability distribution. And as the above referenced post details, this can be done by simply writing down your subjective belief in terms of the Low (L) and High (H) values which bound the range of Bernie’s percentage, the most likely percentage (M) Bernie will get, and your confidence (C) - zero to one - that Bernie’s actual percentage will be in the neighborhood of your best guess or most likely value. In short, your prediction will be a 4-tuple that might look something like – [L, H, M, C] = [51%, 60%, 54%, 0.7].