Forecast: Cloudy With A Chance Of Luck

This post (minus accompanying artwork) originally appeared over at Rooted In Prosperity, the blog about all things MBM. It’s the first in a series of weekly posts, where I’ll explore the more philosophical aspects of libertarianism, and how we might apply those lessons to life and work.

This is the first in a series about success and failure. I’m not totally sure how long the series will go, and it might collapse in horrible, ignominious failure before too long. But if I do it right, then you’ll see why that might just be a good thing.

NYU economist Nouriel Roubini had a reputation as a crank. Joe Keohane explains in the Boston Globe:

The United States was about to get hit with a ghastly housing bust, he said. The price of oil was about to skyrocket, and a particularly nasty recession was on its way, bringing with it untold ruin and misery for citizens, bankers, and businesspeople all over the world. The prophesy was dismissed initially as the mutterings of a pessimistic crank. A year later, he was proved right beyond all doubt.

We place great stock in prediction. Think about ESPN’s talking heads, or Jim Cramer, management books, like Jim Collins’s Good to Great. Learning to predict is immensely important. From romance to our technocratic regulatory agencies, predication and illusion of foresight is something we’re endlessly fascinated with. So how is our friend Roubini? Keohane elaborates:

That one big call about the Great Recession gave him an unrivaled platform from which to issue ever more predictions, and a grand job title to match his prominence, but his subsequent predictions suggest that his foresight may be no better than your average man on the street. The curious nature of his fame calls to mind two of economist Edgar Fiedler’s wry rules for economic forecasters: “If you must forecast, forecast often,” he wrote. And: “If you’re ever right, never let ’em forget it.”

It’s simple: Those who correctly predict extreme events tend to have a greater tendency to make extreme predictions; and those who make extreme predictions tend to spend most of the time being wrong — on account of most of their predictions being, well, pretty extreme. There are few occurrences so out of the ordinary that someone, somewhere won’t have seen them coming, even if that person has seldom been right about anything else.

Does that mean the first lesson of failure is to be leery of success? One of the things I appreciated about MBM was its constant focus on results. Success is good, but random success isn’t exactly something to get jazzed about. How you keep your eye focused on sustainable, repeatable success?

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