2/7 Early treatments of these problems, in the 17th century, assumed that people should optimize expected wealth (blue line). If they did, they would voluntarily play this game -- the blue line points up.
But real people didn't behave this way. They declined the offer to play.
3/7 This happened before it was known that expected wealth (blue line) is not what happens over time (long-time limit of any red line).
So people were puzzled.
The solution to this puzzle is called expected-utility theory (EUT), developed in 1738.
4/7 EUT says your perception of wealth is subjective. Effectively, you subconsciously transform wealth non-linearly into an object called utility, and because of the non-linear transformation, expected utility can shrink over time, while expected wealth grows.
5/7 That may all be true, meaning we can think like this if we want.
But Ergodicity Economics points out that there's a simpler explanation for people declining the gamble: over time (though not in expectation), you lose money in this game.
6/7 If you point this out to an economist, often s/he is elated because this is an amazing simplification that (at this level) makes do without psychological or congnitive assumptions. Everything is observable and physical: you just lose money -- why would you play?
7/7 Other economists have internalized the psychological explanation so deeply that they can't see the beauty of this alternative treatment.
Some even get angry and try to discredit or intimidate me, believe it or not.
Let's end with this Blaise Pascal quote.
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1/7 I disagree with the implicit statement by Mervyn King - wondering what @ProfJohnKay thinks - that maximizing expected utility is reasonable in the small world of a simple model.
My critique is more devastating and less palatable: it's a thought error to optimize this object.
2/ In other words, we don't need to make the model more realistic for expected utility maximization to become a bad idea. It's a priori the wrong object, namely: changes in utility are non-ergodic. Their expectation value has no physical meaning for an individual decision maker.
3/ I'm sorry if this ruins formal economics, but it's time we talked about it like grown-ups: the economic formalism is unacceptable from a quantitative-science point of view.
Before it's worth discussing how realistic it is, we have to correct the flaws in its implied physics.
Friedemann Schulz von Thun came up with a way of clarifying things people say.
In his scheme, any statement is dissected into four components
* factual
* self-revelation
* relationship
* appeal
2/9
The speaker, intentionally or not, sends messages on all of these levels.
The listener, intentionally or not, hears messages on all of these levels.
3/9
Communication problems arise when we confuse different levels. My intention may be to make a purely factual statement, and I may fail to consider its relationship content. That can be hurtful.
1/14
More on @soniasodha's Analysis program from last night.
@ReicherStephen was wonderfully clear. He says there's a "classic" view of humans now, according to which we are psychological frail, biased, faulty. We cannot cope with emergencies. bbc.co.uk/programmes/m00…
2/ This view, he says, is contradicted by the evidence. People don't tend to panic in emergency situations but act rather soberly and sensibly.
To me, that makes perfect sense: evolution would have swiftly got rid of us if our psychology failed us whenever we needed it the most.
3/ It also chimes with what we found in economics: the narrative is one of irrational humans, but when we check, the evidence had a tendency to evaporate, and models that take people's situations into account tend to predict actions correctly.
1/4 Like I said yesterday: it's a cliff-hanger. Let's see what @soniasodha has got for us on Monday.
My recollection: the UK's modeling at the time was catastrophically wrong - "UK 4 weeks behind Italy, and 5-6 days doubling time."
That's on the record (and it was wrong).
2/4 These numbers seemed to come out of @neil_ferguson's model. Then some model assumption was changed, and estimated deaths became more realistic (500,000). No one knew why because the model code was unpublished. It seemed like robustness hadn't been checked.
3/4 I remember someone claimed the change was due to previously underestimating hospitalizations by a factor 2. I found that strange because the pandemic was growing by a factor 2 every 2.5 days. So healthcare system collapse would just move back or forth by ~2.5 days.