Chapter Summary 17: We extract the effect of size on the degradation of the expectation of a random variable, from nonlinear response. The method is general and allows to show the “small is beautiful” or “decentralized is effective” or “a diverse ecology is safer” effect from a response to a stochastic stressor and prove stochastic diseconomies of scale and concentration (with as example the Irish potato famine and GMOs). We apply the methodology to environmental harm using standard sigmoid dose-response to show the need to split sources of pollution across independent (nonsynergetic) pollutants.
Nassim recently posted a document called “Skepticism” on Facebook.
He had this to say about it:
Something people don’t get: more skepticism about climate models should lead to more “green” ecological conservationist policies not more lax pro-pollution ones. Why? Simply, uncertainty about the models increases fragility (and thickens the left tail), no matter what the benefits can be in the right tail. Added the section to the precautionary principle. Please discuss but stick to rigor and avoid buzzwords. (Also do not think that the idea is falling from the sky: it is a mere application of the fragility theorems).
The Skin In The Game Heuristic for Protection Against Tail Events
Constantine Sandis Oxford Brooks
Nassim Nicholas Taleb NYU-Poly; Université Paris I Panthéon-Sorbonne – Centre d’Economie de la Sorbonne (CES)
July 30, 2013
Abstract: Standard economic theory makes an allowance for the agency problem, but not the compounding of moral hazard in the presence of informational opacity, particularly in what concerns high-impact events in fat tailed domains. But the ancients did; so did many aspects of moral philosophy. We propose a global and morally mandatory heuristic that anyone involved in an action which can possibly generate harm for others, even probabilistically, should be required to be exposed to some damage, regardless of context. While perhaps not sufficient, the heuristic is certainly necessary hence mandatory. It is supposed to counter risk hiding and transfer in the tails. We link the rule to various philosophical approaches to ethics and moral luck.
I’ve recently read the book Antifragile: Things That Gain From Disorder by Nassim Nicholas Taleb. It’s obviously not a diet book, but the principles in it are highly relevant to weight loss.
But first, a bit of background. We are all familiar with things that are fragile. If you drop a Ming vase from a height, it shatters. Something that is resilient on the other hand, when dropped from a height withstands stress. An example might be an iron bar.
But until now, we didn’t really have a word for something that gets stronger when it’s placed under stress. That’s why Mr Taleb coined the term “antifragile”.
A good example of antifragility is the system of airline safety. Notwithstanding a few recent tragic examples, air travel gets safer and safer every year. The reason being that every time there is a crash, the incident is scrutinised, causes are elucidated and then measures are taken to try and avoid it happening again. Every air crash makes the next one less likely.
In other words, the system is set up to respond positively to negative things. Every bad incident makes the overall system stronger.
Friends, I am presenting this document (summary of recent work) explaining what is wrong with economics models at a conference in France (which is not fully infected with the Anglo-American disease). Please let me know if you find mistakes as I cut/pasted from *Fat Tails & Fragility*.
A Brief Exposition of Violations of Scientific Rigor In Current Economic Modeling
Nassim Nicholas Taleb NYU-Poly Institute
This is a brief summary of the problems discussed in philosophical terms in The Black Swan and Antifragile with a more mathematical exposition in Fat Tails and Antifragility (2013). Most of the text was excerpted from the latter book.
Note that this is not a critique of modern economic modeling from outside, but from within, using mathematics to put the methods claimed under scrutiny.
The message is simple: focus on measurable robustness to model error and convex heuristics, instead of relying on “scientific” measurements and models. For these measurements tend to cause blowups. And we can measure fragility, not quite statistical risks.