Maps of Bounded Rationality: Psychology for Behavioral Economics - Daniel Kahneman (2003).....................4
Judgment under uncertainty: heuristics and biases - Tversky & Kahneman (1974).........................................5
Five pitfalls in decisions about diagnosis and prescribing - Klein (2005)..........................................................7
Hot-cold Empathy Gaps and Medical Decision Making – Loewenstein (2005).................................................7
Bringing probability judgments into policy debates via forecasting tournaments – Tetlock et al (2017)..........9
Superforecasting: How to Upgrade Your Company’s Judgment – Schoemaker & Tetlock (2017).....................9
Scientific communication in a post-truth society – Iyengar & Massey (2018)..................................................9
Self-Serving Justifications: Doing Wrong and Feeling Moral – Shalvi et al (2015)..........................................10
The Denomination Effect – Raghubir & Srivastava (2009).............................................................................10
The effect of coins on spending – Zenkic et al (2020)....................................................................................11
The end of rational economics – Dan Ariely (2009)......................................................................................11
The Framing of Decisions and the Psychology of Choice - Tversky & Kahneman (1981)
This article describes decision problems in which people systematically violate the requirements of
consistency and coherence, and these violations are traced to the psychological principles that
govern the perception of decision problems and the evaluation of options.
Decision problem: the acts or options among which one must choose, the possible outcomes or
consequences of these acts, and the contingencies or conditional probabilities that relate outcomes
to acts.
Decision frame: the decision-maker’s conception of the acts, outcomes, and contingencies
associated with a particular choice.
The theory belonging to decision-making under risk is the expected utility model.
Prospect theory
The modified version of the expected utility model is the prospect theory, in which outcomes are
expressed as positive or negative deviations (gains or losses) from a neutral reference outcome,
which is assigned a value of zero. The second difference for prospect theory involves the treatment
of probabilities. In expected utility theory the utility of an uncertain outcome is weighted by its
probability; in prospect theory the value of an uncertain outcome is multiplied by a decision weight
π(p), which is a monotonic function of p but is not a probability. Π has the following properties:
- Impossible events are discarded, so π(0) = 0
- Low probabilities are overweighted, moderate and high probabilities are underweighted,
and the latter effect is more pronounced than the former
1
, - For any fixed probability ratio q, the ratio of decision weights is closer to unity when the
probabilities are low than when they are high
Problem 3: Imagine that you face the following pair of concurrent decisions.
First examine both decisions, then indicate the options you prefer.
Decision (i). Choose between:
A. a sure gain of $240 [84 percent]
B. 25% chance to gain $1000, and 75% chance to gain nothing [ 16 percent]
Decision (ii). Choose between:
C. a sure loss of $750 113 percent]
D. 75% chance to lose $1000, and 25% chance to lose nothing [87 percent]
The majority choice in decision (i) is risk averse: a riskless
prospect is preferred to a risky prospect of equal or greater
expected value. In contrast, the majority choice in decision
(ii) is risk taking: a risky prospect is preferred to a riskless
prospect of equal expected value. This pattern of risk
aversion in choices involving gains and risk seeking in
choices involving losses is attributable to the properties of v
and π. Because the value function is S-shaped, the value
associated with a gain of $240 is greater than 24 percent of
the value associated with a gain of $1000, and the
(negative) value associated with a loss of $750 is smaller
than 75 percent of the value associated with a loss of
$1000. Thus the shape of the value function contributes to risk aversion in decision (i) and to risk
seeking in decision (ii).
Two phases in the choice process:
1. Initial phase – acts, outcomes, and contingencies are framed
2. Evaluation phase
Mental Accounting Matters - Thaler (1999)
Mental accounting: the set of cognitive operations used by individuals and househoulds to organize,
evaluate, and keep track of financial activities. Three components of mental accounting receive most
attention:
1. Mental accounting and decision-making - how outcomes are perceived and experienced, and
how decisions are made and evaluated
2. Budgeting - the assignment of activities to specific accounts
3. Choice bracketing and dynamic mental accounting - the frequency with which accounts are
evaluated and choice bracketing
Mental accounting suggests that 1 euro is not always 1 euro, the context matters
The objective of the paper is to illustrate how mental accounting matters
The value function
- Is defined over gains and losses relative to some reference point – the focus on changes,
rather than wealth levels as in expected utility theory, reflects the piecemeal nature of
mental accounting. Transactions are often evaluated one at a time, rather than in
conjunction with everything else.
- Both the gain and loss functions display diminishing sensitivity - that is, the gain function is
concave, and the loss function is convex. This feature reflects the basic psychophysical
2
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