Nassim Taleb and Benoit Mandelbrot on the Economy
pbs.org
pbs.org
When asked about what could happen, there was some talk about a default cascade leading to depressed prices [waves arms] and a grocery store can't make payroll because they can't find a bank to give them a loan secured against their inventory. Now, I don't think he's wrong that we could see grocery stores not making payroll, nor that a default cascade could lead to that. I just think that the arm waving part is what saves us all. If things really do get that bad, then new systems will be formed of necessity. For example, some of those grocery store employees could take a portion of their pay in store credit, micro-lenders could come to the aid of the store (micro-lenders that include the employees), barter will happen, illiquid assets will be traded, and so on.
Not that it will be pretty, or that their won't be real pain, but there are ways to eke by.
Also, I think the most telling comment of the interview was when Mandelbrot said that we couldn't calculate the odds of a catastrophe like this. Taken to it's logical conclusion, this kind of means that we can't tell if we should even be paying attention to these two on this matter. (I know. Mandelbrot. But even Homer sometimes nods.)
In that case, it also means you don't know if you should be paying attention to anyone.
Not just "getting store credit".
Anyways, that's how I'm reading it. Definitely thought provoking. Taleb's piece on Edge.org last month is insanely detailed for anyone looking for more:
Wasn't a whole lot more than them explaining that the system is very complex and hard to predict, and worringly prone to catastrophic events.
Basically, we need to give up some performance and uncouple interacting elements to get more resilient system.
Is predicting the result of a coin toss complicated?
Analogy aside, I don't think one can compare the two. Economics deals with a huge (huge!) quantity of information in doing a prediction. If there was a human that could somehow process all the news, weather forecasts, CEO interviews and financial information, I don't think it would be that hard for him to make predictions, even on a global scale. The issue is that we attempt to capture all this complexity through a handful of insufficient abstractions. It works sometimes. Sometimes it doesn't, much like predicting the weather from a barometer.
If all that information would be quantifiable numerically (syndicate pressure = 0.34) I'm confident that we would have good models and predictions. Models in economy share a lot of the pain of models in biology.
In contrast, for predicting the detail of fluid turbulence or mathematical chaos, the problems are very easy to state, and there is very little information to process. Their mathematical solution and their numerical stability is what makes them complicated.
Aimed at a somewhat more advanced audience.:-)