After reading Antifragile, I got a bit concerned about the economics model. So this just a first attempt to explain why.

While I’m not proposing any changes right now, I think we should thoroughly discuss the subject and make sure everything in the stability model takes into account the proper domain.

These concepts were made by NassimTaleb who divides the world of randomness in mediocristan and extremistan.

**Mediocristan**

Is a place where everything is close to the average, subject to gravity for instance, the bell curve works perfectly here.

Example:

Assume that you round up a thousand people randomly selected from the general population and have them stand next to one another in a stadium. You can even include Frenchmen (but please, not too many out of consideration for the others in the group), Mafia members, non-Mafia members, and vegetarians.

Imagine the heaviest person you can think of and add him to that sample. Assuming he weighs three times the average, between four hundred and five hundred pounds, he will rarely represent more than a very small fraction of the weight of the entire population (in this case, about a half of a percent).

You can get even more aggressive. If you picked the heaviest biologically possible human on the planet (who yet can still be called a human), he would not represent more than, say, 0.6 percent of the total, a very negligible increase. And if you had ten thousand persons, his contribution would be vanishingly small.

In the utopian province of Mediocristan, particular events don’t contribute much individually—only collectively. I can state the supreme law of Mediocristan as follows: When your sample is large, no single instance will significantly change the aggregate or the total. The largest observation will remain impressive, but eventually insignificant, to the sum.

**Extremistan**

This is the domain of information (book sales, stock markets etc…), *where even if you increase your sample size you won’t be able to know it’s true statistical properties, that doesn’t mean the past is irrelevant but it is insufficient to make any useful prediction.*

Fat tails might be disguised as normal distribution for a long time until a single event changes everything.

In Extremistan, inequalities are such that one single observation can disproportionately impact the aggregate, or the total.

Another way to say it is that social quantities are informational, not physical: you cannot touch them. Money in a bank account is something important, but certainly not physical. As such it can take any value without necessitating the expenditure of energy. It is just a number!

Example:

Consider by comparison the net worth of the thousand people you lined up in the stadium. Add to them the wealthiest person to be found on the planet—say, Bill Gates, the founder of Microsoft. Assume his net worth to be close to $80 billion—with the total capital of the others around a few million. How much of the total wealth would he represent? 99.9 percent? Indeed, all the others would represent no more than a rounding error for his net worth, the variation of his personal portfolio over the past second. For someone’s weight to represent such a share, he would need to weigh fifty million pounds!

If you are dealing with quantities from Extremistan, you will have trouble figuring out the average from any sample since it can depend so much on one single observation. The idea is not more difficult than that. In Extremistan, one unit can easily affect the total in a disproportionate way.

In this world, you should always be suspicious of the knowledge you derive from data.

Here is graph showing how an increase in sample size works great in mediocristan but terribly in extremistan.

You can still have more erratic variations on larger samples.