Sunday, December 13, 2015


A gratis copy of Philip Tetlock and Dan Gardner's new book, Superforecasting, arrived a couple months ago, just before it was published. It's been sitting on my desk until now. With a title like "Superforcasting," perhaps I subconsciously thought it would be pop puffery and delayed looking at it. If so, I was wrong. It's a winner.

Superforecasting is in the tradition of Nate Silver's The Signal and the Noisebut whereas Silver has little expertise (except in politics, baseball and poker, which he knows well) and goes for breadth rather than depth, Tetlock has significant expertise (his own pioneering research, on which his book is built) and goes for depth. Tetlock's emphasis throughout is on just one question: What makes good forecasters good?

Superforecasting is mostly about probabilistic event forecasting, for events much more challenging than those that we econometricians and statisticians typically consider, and for which there is often no direct historical data (e.g., conditional on information available at this moment, what is the probability that Google files for bankruptcy by December 31, 2035?). Nevertheless it contains many valuable lessons for us in forecast construction, evaluation, combination, updating, etc.

You can expect several posts on aspects of Superforecasting in the new year as I re-read it. For now I just wanted to bring it to your attention in case you missed it. Really nice.

1 comment:

  1. I'm currently reading it, too, and I really like it. What I find interesting is how it relates to the discussion on "structural" vs. "reduced-form" modelling. Any opinion?


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