Joe has just as much food as he needs, though he would enjoy having some extra. Professor Mephistopheles offers him a bet, where Joe can flip a coin, and if he wins, he will have 3 times as much food as he needs, but if he loses, he will die from hunger. Joe refuses the bet.
Professor Mephistopheles publishes a scientific article about Joe’s irrationality: he seems to care mostly about his food, and yet he refuses a bet which increases his expected amount of food. A new scientific controversy is born...
No, what you are presenting there is the traditional theory. Joe’s behaviour is perfectly explained by him being an expected utility maximiser—you’ve shown that his utility function is concave in food. People haven’t thought that Joe’s behaviour is irrational, ever since Bernoulli.
What I’m saying is that that traditional theory is insufficient to explain people’s betting behaviour. i.e. the monetary variants of “dying from hunger” and “having 3 times more than he needs” do not explain human behaviour.
I am probably missing something, but what exactly is the difference between money and food, if Joe in my example uses money to buy food?
For an average Joe, the utility function is also concave in money, isn’t it? A smart person could use one dollar to buy themselves a food, and another dollar to start a new software company, making them a billionaire in a few years… but for the average Joe, the difference between $1 and $2 is probably a difference between basic food, and basic food plus a cookie.
The post doesn’t deny that the utility function is concave, but it says it can’t reasonable be that much concave as needed to explain rejecting +55/-50 even odds bet with 15,000 on the gambler’s account.
What I’m saying is that you’ve grasped how risk aversion is traditionally modelled: though the gain in terms of units is the same as the loss, the consequences of losing are much worse than the consequences of winning (ie being homeless versus owning a second home).
My point is that if you use that model to explain why people turn down small bets (50-50 on winning $55, losing $50 when the people are reasonably well off), then the model predicts stupidly risk aversive behaviour for larger bets, that don’t correspond to what people do in practice.
Shorter version:
Joe has just as much food as he needs, though he would enjoy having some extra. Professor Mephistopheles offers him a bet, where Joe can flip a coin, and if he wins, he will have 3 times as much food as he needs, but if he loses, he will die from hunger. Joe refuses the bet.
Professor Mephistopheles publishes a scientific article about Joe’s irrationality: he seems to care mostly about his food, and yet he refuses a bet which increases his expected amount of food. A new scientific controversy is born...
No, what you are presenting there is the traditional theory. Joe’s behaviour is perfectly explained by him being an expected utility maximiser—you’ve shown that his utility function is concave in food. People haven’t thought that Joe’s behaviour is irrational, ever since Bernoulli.
What I’m saying is that that traditional theory is insufficient to explain people’s betting behaviour. i.e. the monetary variants of “dying from hunger” and “having 3 times more than he needs” do not explain human behaviour.
I am probably missing something, but what exactly is the difference between money and food, if Joe in my example uses money to buy food?
For an average Joe, the utility function is also concave in money, isn’t it? A smart person could use one dollar to buy themselves a food, and another dollar to start a new software company, making them a billionaire in a few years… but for the average Joe, the difference between $1 and $2 is probably a difference between basic food, and basic food plus a cookie.
The post doesn’t deny that the utility function is concave, but it says it can’t reasonable be that much concave as needed to explain rejecting +55/-50 even odds bet with 15,000 on the gambler’s account.
What I’m saying is that you’ve grasped how risk aversion is traditionally modelled: though the gain in terms of units is the same as the loss, the consequences of losing are much worse than the consequences of winning (ie being homeless versus owning a second home).
My point is that if you use that model to explain why people turn down small bets (50-50 on winning $55, losing $50 when the people are reasonably well off), then the model predicts stupidly risk aversive behaviour for larger bets, that don’t correspond to what people do in practice.