2016 Ehrlich Awards For Wrong Predictions

It's time for the fifth annual giving of the Ehrlich Awards, which round the start of each year go to the most amusingly or staggeringly wrong predictions I observe in any field of interest relating to the previous twelve months.  The Ehrlichs are named for Paul Ehrlich, the evangelist of ecological end-times who put me on a path to a lifetime of health scepticism of dark green gloomery when he not just lost a famous bet with economist Julian Simon but also gave poor excuses for the defeat. For the past editions click the Ehrlich Awards tab at the bottom, and for the ground rules see the 2012 edition.

As usual I should note my own predictive efforts are hardly perfect, but I had a pretty good year in 2016, missing by only two on the Coalition's national Reps seat tally (for example).  I did wrongly predict two Reps seats in my own home state, which was embarrassing, though I did indicate those were quite uncertain.

Two areas of widespread predictive failure that will dominate these Awards were the US election and Senate reform.  They weren't the only ones I noticed.  For instance the late Bob Ellis made a bold bid for posthumous glory with "It is likely, though not certain, that Malcolm Turnbull will lose his seat" - Turnbull won his seat 68:32 with a trivial 1.2% swing against him.  But I think the two I've mentioned are the most interesting ones and I've decided to make the US election case the dishonourable mentions, saving Senate reform for the medals.

Trump Wins: Another Major Poll And Modelling Failure

Well here we are again.  As with the UK election, as with Brexit, as with many other voluntary voting elections we have an unexpected result with the election of Donald Trump as the next President of the USA.  Pollsters are in disrepute because most had Clinton with a modest popular-vote lead, but overconfident modellers deserve their share of the blame for the level of public surprise at the result.

A few days ago, Nate Silver of fivethirtyeight was the target of a terrible Huffington Post article and an argument broke out about whether it was more accurate to say Donald Trump had about a one in three chance of becoming President, or virtually no chance at all.  HuffPo was to double down with this rather pretentious piece by a stats prof accusing Silver of overstimating Trump's chances - a piece that has proved to have an exceedingly short shelf life indeed.  Silver's model might not look crash hot in the wake of what has happened, but it still looks a great deal better than those that were saying Trump had only a 1% chance of winning.