In his speech The dog and the frisbee, Andrew Haldane argues that simple models often outperform complex models in complex situations. He cites as examples sports prediction, diagnosing heart attacks, locating serial criminals, picking stocks, and understanding spending patterns. The gist of his argument is this:
Complex environments often instead call for simple decision rules. That is because these rules are more robust to ignorance.
And yet behind every complex set of rules is a paper showing that it outperforms simple rules, under conditions of its author’s choosing. That is, the person proposing the complex model picks the scenarios for comparison. Unfortunately, the world throws at us scenarios not of our choosing. Simpler methods may perform better when model assumptions are violated. And model assumptions are always violated, at least to some extent.