If the concept of ergodicity introduced here intrigues you, I highly recommend reading the Nature paper "The Ergodicity Problem In Economics": https://www.nature.com/articles/s41567-019-0732-0
The ergodicity problem in economics
Ole Peters
2019 · Nature Physics
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This is essentially an explanation of "absorbing barriers" [1] from ergodicity economics [2]. In ergodic systems, the ensemble average and time average are equivalent, but in non-ergodic systems (most of real life) they aren't. In non-ergodic systems, E[X] [3] is path-dependent. An absorbing barrier is like going all-in on a hand in poker and losing - you lose your entire bankroll, are out of the game, you stop progressing and have no more iterations. Your E[X] no longer incorporates the set of all possible steps or outcomes (ensemble average), but only the ones you actually experienced before incurring the absorbing barrier (time/path dependent average). As a result your…
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real-life E[X] materially differs from your theoretical one. The lesson is that long-term survival should anticipate absorbing barriers, prioritize avoiding them, and build deep buffers against them (cash on hand, etc). [1]:https://en.wikipedia.org/wiki/Absorbing_barrier_(finance) [2]:https://ergodicityeconomics.com/ [3]:https://en.wikipedia.org/wiki/Expected_value [4]:https://www.nature.com/articles/s41567-019-0732-0
Time flies when you're having fun but it was less than four years ago: https://www.nature.com/articles/s41567-019-0732-0 This quote tells you all you need to know about the author's ability to understand things: "my second criticism is more severe and I’m unable to resolve it: in maximizing the expectation value — an ensemble average over all possible outcomes of the gamble — expected utility theory implicitly assumes that individuals can interact with copies of themselves, effectively in parallel universes (the other members of the ensemble)."
> [VC] economics come from the few huge outcomes where founders also have a life changing outcome. Also, gambling has a negative expected value, VCs get more shots on goal, so the typical outcome of a VC could approach that of the average of the industry. (It doesn't, but that's for other reasons.) Founders can't because they have too few shots on goal. Suppose that I'll give you a 10% chance at $100k if you pay me $1k. If you can take that offer "enough" times, you have reasonable odds of making 5-12x on your money. However, if 100 people take that offer once each, around 90% of them will lose their $1k. (They should pool.) https://www.nature.com/articles/s41567-019-0732-0.pdf
Yes, thank you. This intro doesn't get to the depths of the issue. https://www.nature.com/articles/s41567-019-0732-0, by one of the pioneers of the "egondocity economics" is very nice for both going over the math and the academic history of the error. Given the illustrious history of statistical mechanics into Modern probability theory, information theory, theoretical computer science, etc., it's a real shame Econonomics is still stuck with this bad math. https://aeon.co/ideas/how-ergodicity-reimagines-economics-fo... the pop-sci narrative here really doesn't seem that much an exaggeration. The way non-ergonomics fixes the math and confirms some real-world intuitions is quite profound. And certainly there is a lot to critique with orthodox economics' math. (See https://themountaingoateconomics.com/ for another example.)
I know some ergodic theory, but am not an economist. I cannot verify the veracity of the argument, but the argument itself is new, and not reducible to distinguishing between expected utility and expected value. My comment is based on a Nature article by the author [1]. This is just based on a first reading, so my understanding may not be spot on. The observation here is that the utility function in classical economics is not time-dependent. Time dependence is added-on by effects such as discounting. Discounting function itself may be personal - some investors are in a hurry, some are patient, this is usually taken into account. In contrast, the authors introduce…
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stochastic noise into the __rate of growth of the loss function___ (not the expected wealth). [Equation 7 in the Nature paper]. This makes the evolution of the growth rate function into a Brownian motion. The authors claim that this models individual wealth trajectories better. This is as far as I have got. The underlying dynamical equations for the growth function are different, and the authors' claim is that their model predicts individual trajectories better than classical economics, and does not have to use psychology like behavioral economics. [1]https://www.nature.com/articles/s41567-019-0732-0
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