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Advanced behaveriol economics Flashcards

1
Q

Myopic loss aversion

A

People take more risk if they consider several decisions together than if they take them separately

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2
Q

Risk

A

Probabilities are KNOWN

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3
Q

Uncertainty

A

Probabilities are unknown

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4
Q

Prospect/lottery

A

List of consequences with associated probabilities

Example: (50%:€1 ; 50%:€-0,5)

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5
Q

Preference notations

p>q
p~q

A

p>q p strictly preferred to q

p~q indifference between p and q

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6
Q

Monotonicity

A
  • two lotteries L1 and L2

- if no matter what happens, L1 always gives more than L2, then L1 is preferred to L2

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7
Q

St. Petersburg Paradox

A
  • if you play a game with the EV infinite than in reality people will pat less
  • EV means that an increase in our wealth of €100 feels the same no matter whether we earn €1000 or €9000 per month.
  • Solution: first translate monetary amounts into utilities, or subjective values, of monetary amounts
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8
Q

Certainty equivalent (CE)

A

Outcome that makes a person indifferent between receiving the prospect or receiving CE for sure.

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9
Q

Risk premium

A
  • RP=EV-CE
  • risk premium tells us how much of the expected value of the lottery you are willing to give up in return for getting it for sure instead of facing the risk.
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10
Q

Graph utility

Risk averse

Risk neutral

Risk seeking

A

Risk averse - concave utility

Risk neutral - linear utility

Risk seeking - convex utility

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11
Q

Coefficient of absolute risk aversion

A
  • r(x)= - ú(x)/u(x)
  • when EU holds: the higher the coefficient the more risk averse.
  • r measures the concavity of the function
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12
Q

CARA

U(x)=a-be^-cx

U(x)=a+bx

U(x)=a+be^cx

A

Constant absolute risk aversion

r(x)= c for all x; c is a constant parameter

Decreasing absolute risk aversion may be more plausible than CARA: higher income means lower aversion

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13
Q

CRRA

u(x)=a+bx^1-c

u(x)=a+b ln(x)

u(x)=a-bx^-(c-1)x

A
  • Constant relative risk aversion
  • constant coefficient of relative risk aversion r*(x)= x r(x)=c for all x, c is a constant parameter.
  • higher x means lower r(x) to keep r*(x) constant
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14
Q

Uniqueness of utility

A

Utility in EU is unique up to location a and scale b

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15
Q

Measuring utility:

Certainty equivalent method

A

• fix two outcomes m

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16
Q

Measuring utility:

Probability equivalent method

A

• fix two outcomes m

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17
Q

Descriptive validity EU

A

Does everybody have a utility function u that we can use in the EU formula to predict his/her choices?

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18
Q

EU axioms

A

•Completeness:
For all q,r we have either q>r, or r>q, or both

•transitivity:
For all q, r, s we have: if q >r and r>s, then q>s

•continuity:
For all q,r,s with q>r and r>s there must be a probability p such that (p:q ; 1-p : s) ~ r

•independence: for all q,r,s and all probabilities p w have if q>r then (p:q ; 1-p :s) > (p:r ; 1-p :s), and vice versa

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19
Q

Normative validity of EU

A

Do we think that an individual should satisfy the following three conditions?
-eu axioms

If yes then heb should behave according to EU, and then we think that the EU is normatively valid.

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20
Q

Allais paradox

A
  • Common consequence effect.

* Violation of independence aciom

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21
Q

Common ratio effect

A

•violation of Independence axiom

22
Q

Preference reversal

A
  • violation of procedure invariance

* explanation: scale compatibility

23
Q

Asian disease

A
  • violation of description invariance

* how many people will die?

24
Q

Probability weighting

A
  • SEV(p)= n(pi)xi n=pi
  • pi is probability weighting function

•simple decision weighted utility:
V(p) n(pi)u(xi)
•problem: monotonicity is violated as soon as the prob. Weighting function is non-linear
•solution rank dependent utility

25
Rank-dependent utility (RDU)
Weight attached to a state of nature depends on its probability and on its ranking 1. Compute decision weight 2. Compute the RDU RDU(p)= ni u (xi)
26
Diminishing sensitivity
People become less sensitive to changes in probabilities as they move away from the end-points 0 and 1
27
Asset integration
•means that people integrate gains and losses with their total wealth and all they care about is their total wealth
28
Reflection effect
Preferences for gain-prospects are the opposite of preferences for loss-prospects.
29
Isolation effect
People focus on the components that distinguish the alternatives to choose from and they disregard common components.
30
Original prospect theory
1. Editing: organize and reformulate the outcomes and probabilities 2. Evaluation: using the PT formula of previous slide
31
Cumulative prospect theory
Use RDU for gains and losses
32
Fourfold pattern
- gains with high probabilities: risk averse - gains with low probabilities: risk seeking - losses with high probabilities: risk seeking - losses with low probabilities: risk averse
33
Hedonic framing
* segregate gains * integrate losses * integrate smaller losses with larger gains * segregate small gains from larger losses
34
Acquisition utility
Value of the good obtained relative to its price
35
Transaction utility
Perceived value of the deal; difference between amount paid and reference price
36
House money effect
Less risky with money people already have
37
Diversification heuristic
Hoeveelheid maakt uit?
38
Probabilistic sophistication
People behave as if they attach subjective probabilities to events and then use the models of decision under risk.
39
Ellsberg paradox
Knikkerssss - ambiguity aversion: aversion to not knowing the probabilities. - violation of probabilistic sophistication - does not hold in every type of experiment
40
Comparative ignorance
Ambiguity aversion is driven primarily by a comparison between events or between individuals, and its is greatly reduced or eliminated in the absence of such a comparison.
41
Maxmin expected utility
People do not have a single set of utilities in mind for a prospect but instead they have a set of probability distributions in mind -multiple priors
42
Insensitivity to prior probabilities of outcome
People have the tendency to neglect the base rate as soon as specific information is available.
43
Misconceptions of chance
Having a boy or girl after 4 girl’s people think that the next child will be a boy however the probability is still 50%
44
Misconception of samplesize
Number of days of 60% boys being born in a larger hospital and a small hospital.
45
Misconception of regression to the mean
Even purely by chance, good performance will be followed by worse,and poor performance will be followed by better performance. How motivate employees? - reward after good performance - punish after poor performance If you reward after good performance people go back to their average the next time and than you think that is because of the reward but it is the statistics. People may conclude that punishing works better than praising
46
Conjunction fallacy
Linda is this and this and this What is more likely?
47
Availability heuristic
Biases: - Bias due to retrievability of instances - Biases due te effectiveness of a search set - Biases of imaginability - Illusory correlation
48
Anchoring and adjustment
-insufficient adjustment: phone number Taj Mahal -misconceptions of chance: People overestimate the probability of conjunctive events. People underestimate the probability of disjunctive events. -overconfidence: people are over confident about their estimate.
49
Trade off method
Method to measure utility that does not need any assumptions about the type of probability weighting and also does not need to measure probability weighting
50
Concave Convex
Concave x^ (<1) heuvel Utility: points to risk aversion Pwf: points to risk seeking Convex x^ (1
51
Maxmin EU
AlphaMEU= alpha min EU + (1-alpha) max EU Alpha is the weight given to the expected utility of the worst case scenario
52
QHD
Beta: present bias parameter Constant discounting x=y Decreasing impatience x

Economics (4 decks)

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