1. Prospect Theory

4. 23A i 23B, reference point 23A) Your country is plagued with an outbreak of an exotic Asian disease, which may kill 600 people. You are responsible for making decision about two programs. Which program will you choose: a)Program A: 200 people will be saved for sure b)Program B: 600 will be saved with probability 1/3, nobody will be saved with probability 2/3. 23B) Your country is plagued with an outbreak of an exotic Asian disease, which may kill 600 people. You are responsible for making decision about two programs. Which program will you choose: a)Program A: 400 people will die for sure b)Program B: Nobody will die with probability 1/3, 600 people will die with probability 2/3. Kahneman, Tversky (1979) [framing, Asian disease] Lotteries in 23A) are exactly the same as lotteries in 23B). Framing is different though. People often: Choose program A in 23A Choose program B in 23B

5. Gains and losses Which lottery would you choose – A) sure gain of $ 3 000 – B) 1:3 chance of getting $ 4 000 or nothing Which lottery would you choose – X) sure loss of $ 3 000 – Y) 3:1 chance of losing $ 4 000 or nothing 5

6. Conclusion 1 What matters is not final position, but changes relative to some reference point (status quo) Depending on the reference point a given consequence may be interpreted as gain or loss (framing) People are – Risk prone in the domain of losses – Risk averse in the domain of gains

7. 20.1 i 20.2 (or how we perceive probabilities) 20.1) There is 90 balls in the urn – 30 blue balls and 60 that are either yellow or red. You pick a colour. Then one ball is drawn randomly from the urn. If the colour of the ball drawn and the colour of the ball you chose match, you will win $100. Which coloor do you pick? (One answer) a)Blue b)Yellow 20.2) Continuation: If the colour of the drawn ball is of one the colours you bet on, you win $100. Which colours do you pick? (One answer) a)Blue and Red b)Yellow and Red Ellsberg paradox (1962?) [uncertainty aversion] Many people choose: Blue in 20.1 Yellow and Red in 20.2

8. Why is it strange…

9. 17.1 i 17.2 (or how we perceive objective probabilities) 17.1) Choose one lottery: P=(1 mln, 1) Q=(5 mln, 0.1; 1 mln, 0.89; 0 mln, 0.01) 17.2) Choose one lottery: P’=(1 mln, 0.11; 0 mln, 0.89) Q’=(5 mln, 0.1; 0 mln, 0.9) Kahneman, Tversky (1979) [common consequence effect violation of independence] Many people choose P over Q and Q’ over P’ P better than Q U(1)>0.1*U(5)+0.89*U(1)+0.01*U(0) Substitute for U(0)=0 and rearrange: 0.11*U(1)>0.1*U(5) Hence P’ better than Q’

10. 18.1 i 18.2 (or how we perceive objective probabilities) 18.1) Choose one lottery: P=(3000 PLN, 1) Q=(4000 PLN, 0.8; 0 PLN, 0.2) 18.2) Choose one lottery: P’=(3000 PLN, 0.25; 0 PLN, 0.75) Q’=(4000 PLN, 0.2; 0 PLN, 0.8) Kahneman, Tversky (1979) [common ratio effect, violation of independence] Many people choose P over Q and Q’ over P’ P better than Q U(3)>0.8*U(4)+0.2*U(0) Divide by 4 and substitute for U(0)=0: 0.25*U(3)>0.2*U(4) Hence P’ better than Q’

11. Common consequence violates independence P = (1 mln, 1) P’= (1 mln, 0.11; 0, 0.89) Q = (5 mln, 0.1; 1 mln, 0.89; 0, 0.01) Q’= (5 mln, 0.1; 0, 0.9) If we plug c = 1mln, we get P and Q respectively If we plug c = 0, we get P’ and Q’ respectively

12. Common ratio violates independence P=(3000 PLN, 1) P’=(3000 PLN, 0.25; 0 PLN, 0.75) Q=(4000 PLN, 0.8; 0 PLN, 0.2) Q’=(4000 PLN, 0.2; 0 PLN, 0.8)

13. p1p1 p2p2 1 1 1mln 0 5mln 17.1) Choose one lottery: P=(1 mln, 1) Q=(5 mln, 0.1; 1 mln, 0.89; 0 mln, 0.01) 17.2) Choose one lottery: P’=(1 mln, 0.11; 0 mln, 0.89) Q’=(5 mln, 0.1; 0 mln, 0.9) Common consequence effect in the Machina triangle

14. Fanning out p1p1 p2p2 1 1 1mln 0 5mln

15. Conclusion 2 We often perceive probabilities as if they didn’t conform to the laws of probability – We prefer risk than uncertainty uncertainty aversion (Ellsberg paradox) – Certainty effect - we attach to high a value to certainty (Allais paradox) Maximizing utility may not describe many our choices 15

16. 11 (or endowment effect) 11.1) You are given a new coffee mug (photo below). For what minimal price would you sell it? Give a price between $1-$50. 11.2) There is a coffee mug for sale. For what maximal price would you buy it? Give a price between $1-$50. Kahneman, Knetsch, Thaler (1990) [endowment effect, WTA-WTP disparity] WTA>WTP

17. Conclusion 3 We are reluctant to depart from the status quo We dont’t want to part with what’s ours or what we bought or acquired 17

24. People usually pay more if n=1 Expected utility implies the opposite: 1/3 versus 1/6

26. Famous Zeckhauser’s paradox

27. Conclusion 4 People do not weigh probabilities evenly – They overweigh low probabilities – They underweigh high probabilities

28. Recap Behavior – The context of decision is important (reference point, what is gain, what is loss) – We perceive probabilities in the wrong way (e.g. attach too much priority to a given event) – We are attracted too much to what we have (status quo bias) – We like sure gains, we dislike sure losses – We dislike losses more that we like gains (losses loom larger than gains) Theory – Expected Utility Theory does not acommodate these features 28

33. Probability weighting

34. Exercise