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How to Win at Forecasting
For those interested in forecasting (particularly for political outcomes) as a field of study, Philip Tetlock is a name you should know. Here’s an insightful interview: http://edge.org/conversation/win-at-forecasting. A few of my favorite quotes:
“I naively thought that pundits were in the business of accurately making forecasts” but really they are “flattering the prejudices of their base audience” and routinely “insulate themselves on vague verbiage…cushion themselves with rhetoric”.
To Be a Forecaster, Be a Weatherman
As I say in most all my writings about forecasting and economics: Market behavior is much more like a CEAS (Complex Emergent Adaptive System) than it is a neat and tidy math-based equilibrium model. Here’s a fun piece:
A Dose of Optimism
Mark Mills and Julio Ottino’s Op-Ed in the WSJ on Monday, Jan 30, “The Coming Tech-led Boom,” is a must-read for anyone needing a good dose of optimism to combat persistent media hypochondri-nomics.
A couple teaser paragraphs:
First, demographics. By 2020, America will be younger than both China and the euro zone, if the latter still exists. Youth brings more than a base of workers and taxpayers; it brings the ineluctable energy that propels everything. Amplified and leavened by the experience of their elders, youth and economic scale (the U.S. is still the world’s largest economy) are not to be underestimated, especially in the context of the other two great forces: our culture and educational system.
The American culture is particularly suited to times of tumult and challenge. Culture cannot be changed or copied overnight; it is a feature of a people that has, to use a physics term, high inertia. Ours is distinguished by incontrovertibly powerful features, namely open-mindedness, risk-taking, hard work, playfulness, and, critical for nascent new ideas, a healthy dose of anti-establishment thinking. Where else could an Apple or a Steve Jobs have emerged?
Irene Is a “Teaching Moment” for Economists
I’ve always believed meteorology has been a good way to think about economic forecasting models. Simply, economists can, via statistical analysis, have some visibility on what might happen next, but the system (be it ecological or economical) is so vast and complex we just don’t have the models to know with precision what will happen, even in the immediate future. So, after the Irene panic over the weekend, we instead get headlines like ‘People assume we can predict everything’…; NYT: Experts Misjudged Structure and Next Move…; IRENE: A PERFECT STORM OF HYPE…, and so on. It’s not that the meteorologists did a bad job—they’re just limited in what they can do, and in a situation where lives are on the line they will err on the side of caution.
This is basically—almost precisely—how to think about economic forecasts. Are we headed for another recession? Maybe. My sense is probably not. But recent weak economic data don’t guarantee anything either way. Quarterly and monthly data especially is lumpy, and never moves in a straight line. So, you get a headline like this that surprised a lot of folks this week:
Consumer Spending in U.S. Climbs More Than Forecast on Purchases of Autos — Bloomberg
Statistical economic analysis in forecasting, even just a month ahead, is at this point a lot like meteorology—the system is too complex to predict with perfect accuracy.
