Week 2: Rationality and Behavioral Economics

Question 1

rationality vs. bounded rationality

Answer 1

Rationality: consistency between preferences and choice.
Preferences - you can express indifference, but can’t NOT have a preference (completeness)

Bounded Rationality: any behavior that departs from rational theory (changing preferences)

Question 2

incomplete preferences (defn and example)

Answer 2

making up preferences on the spot, and those preferences being random.

Example: Bendor’s Muddling Through - this is one way of tackling the issue of incomplete preferences and there are many others

Question 3

(Quasi-)Hyperbolic Discounting

Answer 3

we discount all future periods by an additional factor (beta). people are impatient / present really matters. also known as beta-delta model. If Beta is small (or if impatience is large), then u1 becomes negative and you don’t invest. your impatience moves along with you in time – you will also be impatient tomorrow, which could unravel the plans you set up for today.

Example: paying not to go to the gym (DellaVigna and Malmendier) - only 20% of monthly users got their money’s worth. Why? monthly contract as a commitment to exercise. Authors think it’s b/c of people’s overconfidence.

Example: I’ll work on homework tomorrow.
To fix this, we need commitment mechanisms like deadlines.

Question 4

Law of Small Numbers

Answer 4

misperception of regression to the mean

intuitively, people are bad statisticians in decision-making. we are likely to over-observe from a few observations. over-inferring based on recent events. you don’t observe regression to the mean (misperceiving regression to the mean)

example - Israeli air force trainers

Question 5

hot hand

Answer 5

making lots of baskets in a row (“on a streak”) – you can come up with strings of heads/tails yet on average – the probability is still the same

Question 6

belief perseverance and confirmatory bias

Answer 6

people who come in with prior beliefs will process the same information differently (overemphasize data that reinforces their idea) - often when presented with evidence just cherry pick to galvanize their pre-existing belief

Question 7

Anchoring and Confirmation bias

Answer 7

Example: reading a paper about death sentences, you’ll read the paper according to your pre-existing biases

Question 8

Availability Heuristic

Answer 8

judgement compromised by importance of examples. related to hindsight bias. estimates are based on what sticks out in memory. people overweight things covered in media or personal experience.

Example: perception that murder is more common in US than suicide because murder is in the news a lot. Suicide is actually more common in US.

Question 9

Reference dependence

Answer 9

loss aversion - losses matter more than gains. utility function kinked around arbitrary reference point – the reference point can be changed.

Related to this is the endowment effect and status quo bias (mug experiments) and sunk cost fallacy.

Example: Mas. police officer union. In NJ, fire and police forces can bargain collectively, but can’t strike. This leaves to final offer arbitration. Probability of conviction did not change (increased clearances are not due to arresting the innocent). Probability of incarceration increased after union win (better evidence collection, cooperation with prosecutors?)

Question 10

Sunk Cost fallacy.

Answer 10

idea that just because you started a project, you need to finish it. huge perceived lost.

Question 11

Preferences

Answer 11

having complete and binary comparisons over alternatives (so that we can assign numbers to preferences)

Question 12

Representativeness Heuristic

Answer 12

Example - Rare disease, p that you test + is 5% (false positive). if you do have disease, p that test is false negative is 10%.

We can’t determine without knowing the probability that you have the disease (the base rate)

Question 13

Fairness Motive

Answer 13

example: First player offers share of money; second player either accepts or forces both to receive zero. Offers of 25% are routinely rejected.

Question 14

Where does bounded rationality come from?

Answer 14

Cohen 2005

Humans evolved to treat proximate choices differently. The brain is a confederation. Prefrontal cortex = impersonal decisions. Subcortical = personal decisions. So then, professionalism can be seen as a response.

Question 15

Endowment Effect

Answer 15

Group that receives mugs values them at 7 USD, those that don’t receive mugs value them at $3.50.

Question 16

Loss aversion

Answer 16

value gains more than losses

Question 17

Status Quo bias

Answer 17

e.g. mugs and candy given worth same value. ask those who want to exchange and very few people exchange.

Question 18

Hindsight bias

Answer 18

Example: sports writing - victory for Team X is inevitable (after victory has occurred)

Question 19

Condorcet Paradox

Answer 19

Condorcet Paradox. Individual rationality doesn’t always translate to collective rationality.

Question 20

Prospect Theory

Answer 20

Your preferences are not stable (arbitrariness of framing)
Different representations of the same problem yield different results
Critiques preference assumptions of rationality
Results depend on whether one “frames” a problem as being one of gain or loss

In a loss situation, we become risk acceptant
In a gain situation, we become risk averse

Question 21

dominant vs. dominated vs nash equilbrium

Answer 21

Dominant Strategies: The best strategy regardless of opponent’s move

Dominated Strategies: A bad strategy regardless of opponent’s move

Nash Equilibrium: The best response, given opponent’s best strategy, Possibly not unique

Question 22

High m if:
Noise is:
There is single/multiple principals
There is single/multiple agent(s)
Number of tasks is:
Frequency of Interaction:
There is competition with/without collusion

Answer 22

Noise is: low
There is single
principals
There is single agent(s)
Number of tasks is: low 
Frequency of Interaction: high
There is competition without collusion