20. Uncertainty

MIT 14.01 Principles of Microeconomics, Fall 2018
Instructor: Prof. Jonathan Gruber
View the complete course: ocw.mit.edu/14-01F18
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This video explains the economic concept of decision making under uncertainty.
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[@Dr_Tanvi_Sinha]

What a glorious lecture. Historic. I've listened to this on flights a hundred million times and yet learn something new with each view. What a beauty economics is 😊

[@yashchugh9132]

@34:38 shouldn't the cost be 398 since at a cost of 399 the 25 yr old male would just be indifferent between the choices, but at 398 his E(u) would be better if he's insured? Phenomenal work th0 MIT ❤️

[@Tactical_DZ]

Really good lesson, thank you sir.

[@princessjudii]

This is super helpful

[@OG-NASA]

Superb.

[@ghanshyamgupta5385]

Awesome lecture. Thank you professor🙏

[@economicclasses]

Watching from kashmir in 2020 at 2g speed in 21 century

[@apnaustaad9818]

Nothing can beat our appetite to learn! Let the whole world know that!

[@ImVedanshAgarwal]

From up, ditching college zoom lectures and watching this .

[@kiranfhh9059]

Kashmiri hindus watching this as refugees in their own country, victims of religious violence .

[@avinashdwivedi2015]

@@kiranfhh9059 wtf?

[@kiranfhh9059]

@@avinashdwivedi2015 ?

[@groenewilde]

I loved the lecture, but I do have 1 short question; all of the examples used have probability values, which is calculated risk, not Knightian uncertainty. How do we deal with that in economics?

[@juansolis8891]

Knightian uncertainty is not dealt with, it's ignored and economists work with theorems / idealized situations just to "illustrate principles" or "get insight into situations".

[@vanessaverner8480]

I am taking an online class. Some teachers to not post an online lecture. Thank You,

[@VictoriaLaRocque]

I do not get the idea of splitting one month's insurance if a risk of getting hit by car is not evaluated per month too. Otherwise, you should calculate 40 000 x times you get your salary under the period that the risk of 0,01 is for, which is probably the whole life, so that gives a tiny sum of some dollars per month, far below 399

[@nurgulturkmen5508]

how do we know we won 125$ ? at 08:00

[@yellowusbrickus4821]

He is just calculating the expected utility of the bet, which is the sum of each outcome's utility multiplied by the probability of that outcome. So if he wins, he has 100+125=$225 and that gives a utility of root(225) and that has a 50% probability, so expected utility = root(225)/2 +root (100-100)/2.

[@giles1358]

Hi guys. Hopefully someone can help clarify something here. At around 9:05 he says that the Expected Utility is less than the Initial utility, but surely that is based on his given utility function. Isn't that utility function just like a cost function, it could be anything, he's just plucked that function out of the air? Or is that specific equation something that needs to be remembered.

[@rocky171986]

The specific square root functional form is just a choice of a utility function, but this choice was made because it shows a diminishing return of utility leading to the risk adverse conclusion. Basically, the "shape" of the utility function is more important in explaining the qualitative expectation of the behavior, the exact numbers e.g. bet rewards would depend on the exact form of the utility function. That said, utility functions in real life are extremely difficult to model and in real life, empirical estimates are usually made.

[@giles1358]

@@rocky171986 brilliant, thank you.

[@mashailiftikhar9538]

how do we get 43.74 cents?

[@henryniu6037]

If you go for this gamble, the expected utility you would get is 7.5, which is equivalent to $7.5^2 = $56.25 in terms of wealth (given the utility function: u^2 = c). As compared to the original utility you have which is 10 (i.e. $10^2 = $100 in term of wealth), the difference is $100 - $56.25 = $43.75, which means the fact that you are indifferent to attend the bet or pay $43.75 for not attending the bet. As a result, $43.74 is the price that you will definitely be willing to pay for not going for that gamble.

[@mashailiftikhar9538]

@@henryniu6037 thank you so much

[@nabsungkar]

@@henryniu6037 thank you so much

[@Risk_and_Reward_Youtube]

I understood the first 5 minutes, and then my expected utility went to 0

[@sreyanshuchaterjee3962]

Ref: Thinking Fast and Thinking Slow

[@yominonnn]

Great reference. Note Expected Utility Theory (lecture) != Prospect Theory (Kahnemann). One is about risk aversion for rational agent vs another is loss aversion of people.

[@dandykaufman2]

we need medicare for all, professor

[@MachaSavageBunny]

Sometimes it made me think that the teachers are so smart they made me wonder, becaus they're so on the topic, like they can be on a topic for a very long time.😂

[@purple_hyacinth536]

At 23:52, why is the utility root 112.5?

[@thepetris]

Because that is the utility in case you win, which is given by the root of the total amount of money you would be having in that case. That is, the root of your initial wealth (100) + the amount you would win (12.50), hence root 112.5

[@purple_hyacinth536]

Oh so the winning amount is 12.50 and not 1,250? Got it now. Misunderstood that one. Thanks!

[@juansolis8891]

why is utility the square root?

[@cherrymarriedindiscord1404]

It was just a useful example because the model tampers off You can find other things if you take the time to model it but I'm not an expert at all so I hope someone else who is more acknowledged will try to answer you too

[@juansolis8891]

@@cherrymarriedindiscord1404 thank you

[@Cam-lh7nr]

I think that you neglect to consider the addictive property of gambling. Much like smoking. Everyone is not ignorant, entertainment is certainly coming close, but addiction seems to me the most plausible explanation, especially when I consider the types of regular lottery participants you mention.

[@susieroberts8175]

Why is the function 'concave'? Looks convex to me ...

[@Cam-lh7nr]

Convex has a negative distance from the linear segment, concave a positive. Linear functions are both convex and concave