The Boston Globe's take on the frequent misses of the formerly doomsaying economist Nouriel Roubini is discouraging for those who think they've found the right forecasting formula--and for everyone else looking for somebody who has.
Joe Keohane cites especially the work of the political scientist Philip Tetlock, who revealed that the formula for successful political prophecy is to make frequent and bold claims. People will remember only the correct calls. Economic forecasting is little different, according to two academic economists, Jerker Denrell and Christina Fang:
Economists who had a better record at calling extreme events had a worse record in general. "The analyst with the largest number as well as the highest proportion of accurate and extreme forecasts," they wrote, "had, by far, the worst forecasting record."
Their findings are also discouraging for those of us using history to inspire strategy. Success, Denrell has found,
is an especially bad teacher. In 2003 he published a paper arguing that when people study success stories exclusively--as many avid devourers of business self-help books do--they come away with a vastly oversimplified idea of what it takes to succeed. This is because success is what economists refer to as a "noisy signal." It's chancy, fickle, and composed of so many moving parts that any one is basically meaningless in the context of the real world. By studying what successful ventures have in common (persistence, for instance), people miss the invaluable lessons contained in the far more common experience of failure. They ignore the high likelihood that a company will flop--the base rate--and wind up wildly overestimating the chances of success.
Maybe that's why there are so few super-rich economists, and zero historians of technology or business. In all the lists of billionaires I've seen, it's hard to find one who made his or her fortune by relatively accurate predictions of technology or markets. The greatest fundamental investor, Warren Buffett, is famous for declaring that he never puts money in anything so advanced it's hard to understand. George Soros' coups are closer to high-stakes poker than to crystal-gazing. (Consider his stand on gold.) There are a few consistent hedge fund geniuses like Renaissance Technologies' James Simons, but of course they rarely publish anything about their methods, and their prowess appears to rest on recruiting brilliant staffs to help them discover new market anomalies as the value of successful strategies decays. And even Simons' newer funds have been disappointing performers. (The funds you really would like to buy, always seem to be closed to new investors, as that doctor you've heard so much about isn't accepting further patients.)
Keohane and Denrell certainly have a point about how misleading examples can be, but the positive-thinking genre has survived even its ablest debunkers intact--curiously like astrology, which would seem to pose limits to the optimistic human will.
The challenge in thinking about the future consists of harnessing simultaneously our expansive and cautionary minds. Jeff Bezos, taking an enormous risk on the future of the Web and giving up a lucrative hedge fund job, made a veteran tech skeptic his first employee, according to Wired. The programmer, Shel Kaphan,
has a reputation among the engineering staff at Amazon.com as the prototypical pessimist, a geek convinced that the company's systems are always on the verge of implosion. He came by his doomsaying honestly - he had worked for at least a dozen companies before Amazon.com, including failed start-ups and bureaucratically inept monsters. Shortly before he and Bezos met he had left Kaleida Labs, an ill-fated Apple spin-off, which makes it all the more remarkable that he almost immediately found Bezos trustworthy - so trustworthy, in fact, that Kaphan agreed in short order to relocate to Seattle.
So it's not enough to say that most things fail. The research cited by Keohane suggests that consistent pessimism also isn't terribly accurate or helpful. In fact there's a bright side to humanity's inability to predict the future accurately, which I recently explored here.