CP

• Making an assumption based on observation

• Assumption: choices reveal latent preferences

  • If Anna chooses an apple over an orange, Anna prefers the apple

• Questions asked:

  • How to spend money

  • How to allocate effort

  • How to plan for the future

• Answered by decision theory, which is used by

  • Economics: How to make “optimal” choice

  • Psychology: How people actually make choices

Which leads to consequences for social policies

• Theory on how people SHOULD make decisions (rationally)

• WARP: Weak axiom of revealed preferece/Completeness assumption

  • When given the choice between A and B, we assume that the consumer prefers

    • A

    • B

    • Neiter/No preference

  • Violation of WARP: Consumer prefers both A and B

• Independence of irrelevant alternatives assumption (IIA):

  • Assumption: If someone prefers A over B, this preference will hold up consistently in every circumstance

  • Violation: If someone prefers A over B, but will choose B if they have to choose between A and a grape or B and a grape

• Transitivity Assumption

  • Assumption: Concluding that if A > B, and B > C, then A > C

  • Violation: the money pump thought experiment

    • If object ranking is not rational, a person would want to trade B for A, A for C and C for B -> this is how people can be exploited

      • Being rational is in ones own best interest, since being irrational opens the gates for being exploited

Choice patterns which satisfy simple, logical assumptions of choice

• Decisions reveal preferences

• Preferences can be ranked/ordered from low to high

• Decisions can be characterized as if the decision maker would maximize their “utility”

• Property in any object that

  • produces benefit, good, wellbeing, happiness, advatage

    • and/or

  • Prevents the happening of mischief, pain, evil, unhappiness

• to the party whose interest is considered

• If we can quantify the pain and pleasuer of decisions, we should choose those decisions which maximize the total expected utility of everyone if affects (maximize pleasure, minimize pain)

• The trolley problem

• According to utilitarianism, we should always choose the option which saves most lives (even by sacrificing one)

• People struggle to act accordingly when they have to actively push someone to their death

• Trolley-dilemma is being used for self-driving cars to decide who should die in case of an accident

• Problems:

  • There are preferences based on age, occupation, animal vs. humans etc.

  • Those preferences are further influenced by culture, i.e. they differ between west/south/east

    -> should cars decide depending on the location where they drive?

• Calculated by multiplying each possible outcome by its likelihood and then summing it together to make a rational decision under risk

• Example:

  • Option A: 50% chance of winning 100.-, 50% chance of winning nothing

  • Option B: Getting 40.- for sure

  • 0.5 x 100 + 0.5 x 0 = 50.- -> 50.- > 40.- -> Rational choice would be choosing option A (expected value optimiser)

• Paradox in relation to expected value

• Choice: a fair coin is tossed

  • If head appears, you win 2 Euros and the game goes on

  • If head appears, you win 4 Euros and the game goes on

  • If head appears, you win 8 Euros and the game goes on

  • etc.

  • The game ends when tails appears

  • How much are you willing to pay?

• Calculating with expected value, it would look like this:

  • .05 x 2 + 0.25 x 4 + 0.125 x 8 etc. -> infinite

  • Accordingly you should be willing to pay an infinite amount of money to play (according to expected value maximizer)

  • Yet, almost no human being is willing to do that

• Possible explanation

  • The value of an item is not based on the price, but rather the utility it yields (i.e. winning 1000.- is more relevant to a poor person than to a rich person, even though it is the same amount of money objectively)

    -> Money chages its value depending on who has it

• Utility: depends on psychology/perception (contrary to value)

• Relationship between utility and value is NOT (necessarily) linear

  -> Chages things around decision making under risk

• Alterantive to the expected value theory/calculation

• Instead of including the actual value, the individual utility is inserted

• I.e. if the utility of earning 40.- is 30, we can then calculate the utility of winning 100 and 0 CHF -> can change the result of the best “rational” decision

  • The difference in utility between 40.- and 100.- might be smaller than the actual difference in value

-> Maximizing utility (rather than value) is also rational, since rationality = sticking to your preferences, being consistent

• Risk aversion: Concave utility function (value > utility)

• Risk neutrality: Linear utility function (value = utility)

• Risk-seeking: Convex utility function (value < utility)

• Risk preferences are not considered irrational (as long as chooser consistently maximises utility)

• There is a context depencence to risk preferences (otherwise risk adverse people would never go to a casino)

• Individual risk preferences can be assessed by presenting different decision problems and always adapting option A (the risky decision) -> depending on the decision pattern you can tell the risk preference of that person

• On average across groups people are rather risk-averse (concave curve)

  • however, not to an extreme, they are around 0.5 risk averse

• People discount value over time by a certain factor

• Can be calculated with the following equation:

  • U(X) = X x e^-kD

    • U(X) = utility of X

    • X = actual value of X (i.e. 20.-)

    • k = discount factor

    • D = delay (i.e 5 days)

• Value of X changes/diminished depending on the Delay and the k factor

• Time preferences are also rational, as long as they are dynamically consistent

• Through choice patterns, the latent time variable k can be made visible

• Inflation (money might lose it’s worth)

• Interest rate over money

• Uncertainity about future wellbeing

• Policies should be aimed at making decision consequences transparent (perfect information)

• No need to help decision makers make decisions

• People would know best what they want

• Libertarian principle of governance