Behavioural Economics 4: Other-regarding Preferences

Question 1

What are other-regarding preferences in behavioural economics?

Answer 1

Other-regarding preferences refer to situations where individuals care not only about their own material payoffs but also about the outcomes of others.

Why it matters:

Challenges the standard self-interest hypothesis: “All individuals are exclusively self-interested.”
Explains behaviours like charitable giving, fairness, reciprocity, and cooperation.
Helps model real-world phenomena like:
Collective action
Wage premiums
Incomplete contracts
Institutional design
Your Note (Slide 1–2):

Based on Fehr & Schmidt (2006)
Understanding behaviour is essential for modelling and policy design.

Question 2

What is the standard self-interest hypothesis and how has it been tested?

Answer 2

Hypothesis:
“All individuals are exclusively self-interested.”

Assumes utility depends only on own material payoff.
Early Support:

Vernon Smith (1962): Experimental markets showed quick convergence to equilibrium under self-interest assumptions.
Challenge:

Over the last 20 years, experiments show many people act fairly, altruistically, or reciprocally, even when self-interest is salient and easy to follow.
Your Note (Slide 3):

Self-interested choice is often obvious, yet people still choose fairness.
Suggests self-interest is not a universal assumption.

Question 3

How do market structures affect the visibility of social preferences?

Answer 3

Explanation:
In competitive markets:

Other-regarding goals are impossible or too costly to pursue.
Behaviour appears self-interested due to structural constraints.
Real-world markets:

Often non-competitive:
Few traders
Informational frictions
Incomplete/enforceable contracts
Implication:

Models assuming social preferences perform better in these settings.
Your Note (Slide 4):

Helps explain wage premiums, contract design, and cooperation.

Question 4

Name and describe the purpose of the four classic experimental games.

Answer 4

Games:

Ultimatum Game (UG) – Tests fairness and negative reciprocity.
Dictator Game (DG) – Tests altruism and fairness without strategic concerns.
Trust Game (TG) – Tests trust and positive reciprocity.
Public Good Game (PGG) – Tests cooperation and conditional reciprocity.
Why these games?

Controlled and simple: easy to understand.
Dominant strategy for self-interest is clear.
Deviations reveal underlying motives.
Your Note (Slide 7):

These games are foundational.
We study their structure, predicted results, actual outcomes, and variations.

Question 5

What are the benefits of using experimental games to study other-regarding preferences?

Answer 5

Concept: Experimental evidence allows us to isolate and test behavioural assumptions under controlled conditions.
Why it matters:

Ensures simplicity and clarity: dominant strategies are easy to identify.
Allows us to infer motives when people deviate from self-interest.
Provides replicable and robust data across cultures and contexts.
Your Note (Slide 7):
These games (UG, DG, TG, PGG) are famous because they allow us to test structure, predicted results, actual behaviour, and extensions.

Question 6

Describe the rules and structure of the Ultimatum Game (UG).

Answer 6

Game Structure (Güth, Schmittberger & Schwarze, 1982):

Two players: Proposer and Responder.
Proposer receives an amount of money S (e.g. £10).
Proposer offers x ∈ [0, S] to the Responder.
Responder can accept or reject the offer:
If accepted: Proposer gets S − x, Responder gets x.
If rejected: Both get £0.
Purpose:

Tests fairness, negative reciprocity, and the self-interest hypothesis.
Your Notes (Slide 9):

Anonymity (“whose identity you do not know”) is crucial to avoid reputation effects.
Framing matters: saying “split” vs “send money” can influence perceived fairness.

Question 7

What does the self-interest hypothesis predict in the Ultimatum Game?

Answer 7

Assumptions:

Both players are rational and care only about material payoff.
Proposer knows Responder is rational and selfish.
Prediction:

Proposer offers the smallest possible amount (>£0).
Responder accepts any positive amount.
Implication:

If players behave differently, it challenges the self-interest hypothesis.

Question 8

What are the standard findings from the Ultimatum Game?

Answer 8

Empirical Findings:

Proposers typically offer 40–50% of the total amount.
Offers <20% are rejected 40–60% of the time.
Interpretation:

Responders are willing to sacrifice money to punish unfairness.
Indicates presence of fairness concerns and negative reciprocity.
Your Notes (Slide 11):

These results contradict the self-interest hypothesis.
Responders do reject low offers that are perceived as unfair.

Question 9

What variations have been tested in the Ultimatum Game and what do they show?

Answer 9

Stakes (Cameron, 1999):

UG with 3 months’ income in Indonesia.
No change in proposer behaviour.
Slight decrease in rejection rates with high stakes.

Culture (Roth et al., 1991):

Japan & Israel: lower offers and rejection rates.
US & Slovenia: higher offers and rejection rates.

Small-Scale Societies (Henrich et al., 2001, 2004):

15 societies across 5 continents.
Huge variation in offers and rejections.
Explained by market exposure and group cooperation norms.

Your Notes (Slide 12):

“Stakes” = size of the endowment (e.g. £10 vs £1000).
Student samples are convenient but not representative.
Cultural context and economic structure matter more than individual traits.

Question 10

Describe the rules and purpose of the Dictator Game (DG).

Answer 10

Game Structure (Forsythe et al., 1994):

Two players: Dictator and Receiver.
Dictator receives an amount S (e.g. £10).
Dictator unilaterally decides how much x ∈ [0, S] to give to the Receiver.
Receiver has no input and must accept the outcome.
Payoffs:
Dictator: S − x
Receiver: x
Purpose:

Tests altruism and fairness without strategic concerns.
Isolates pure other-regarding preferences.
Your Notes (Slide 15):

Incentive compatibility is crucial: if participants suspect deception (e.g. no real receiver), they may behave more selfishly.
No deception is a core principle in experimental economics to preserve trust and data validity.

Question 11

What does the self-interest hypothesis predict in the Dictator Game?

Answer 11

Assumptions:

Dictator is rational and cares only about own material payoff.
Receiver has no power to influence the outcome.
Prediction:

Dictator keeps 100% of the money.
Receiver gets £0.
Implication:

Any positive transfer contradicts the pure self-interest model and suggests altruism or fairness.

Question 12

What are the standard findings from the Dictator Game?

Answer 12

Empirical Findings (Engel, 2011 meta-study):

Dictators give away ~30% of the endowment on average.
Many give non-zero amounts despite no strategic reason to do so.
Interpretation:

Evidence of altruism, fairness, or social norms.
Suggests that people derive utility from giving, even without external pressure.

Question 13

What variations affect behaviour in the Dictator Game?

Answer 13

Key Variations (Engel, 2011):

Stakes: Higher stakes → slightly lower donations.
Student vs Non-student: Non-students give more.
Receiver Deservingness: Charities or “deserving” recipients receive more.
Multiple Receivers: More given per person (contrary to identifiable victim effect).
Gender: Women give and receive more.
Hypothetical vs Real Incentives: No significant difference.
Earned vs Windfall Money: Earned money → lower giving.
Your Notes (Slides 17–18):

“Deserving” = e.g. charities.
Surprising finding: people give more when there are multiple receivers, even though prior research suggests people give less per person in such cases.
Framing the decision as “how much do you want to invest?” can also influence generosity.

Question 14

Describe the rules and purpose of the Trust Game (TG).

Answer 14

Game Structure (Berg, Dickhaut & McCabe, 1995):

Two players: Investor and Trustee.
Investor receives an amount S (e.g. £10).
Investor chooses how much x ∈ [0, S] to send to the Trustee.
The amount sent is tripled (3x).
Trustee decides how much z ∈ [0, 3x] to return to the Investor.
Payoffs:
Investor: S − x + z
Trustee: 3x − z
Purpose:

Tests trust (Investor’s action) and trustworthiness (Trustee’s response).
Also captures positive reciprocity.
Instructions (Slide):
“You have been given £10. You have to decide whether you send money to another player whose identity you don’t know. The amount you send will be multiplied by 3. Then the other player will decide whether they send money back.”

Question 15

What does the self-interest hypothesis predict in the Trust Game?

Answer 15

Assumptions:

Both players are rational and care only about own material payoff.
Prediction:

Trustee will return nothing (z = 0).
Investor anticipates this and sends nothing (x = 0).
Implication:

If any money is sent or returned, it contradicts the pure self-interest model and suggests trust or reciprocity.
Real-World Analogy:

Models situations where one party must act first and trust the other to reciprocate (e.g. lending, partnerships).

Question 16

What are the standard findings from the Trust Game?

Answer 16

Empirical Findings:

Investors send about 50% of their endowment on average.
Trustees often return a portion of the tripled amount.
Substantial variability in both sending and returning behaviour.
Interpretation:

Evidence of trust and positive reciprocity.
Suggests that people are not purely self-interested and are willing to take social risks.

Question 17

What variations affect behaviour in the Trust Game?

Answer 17

Sample Type:

Most studies use WEIRD participants (Western, Educated, Industrialised, Rich, Democratic).
Studies in Germany (Fehr et al., 2002) and the Netherlands (Bellemare & Kroger, 2003) show similar patterns.
Stakes:

Comparing €10 vs €100 → no significant effect on trust or reciprocity.
Demographics:

Some demographic factors influence behaviour, but overall patterns remain stable.

Question 18

Describe the rules and purpose of the Public Good Game (PGG).

Answer 18

Question 19

What does the self-interest hypothesis predict in the Public Good Game?

Answer 19

Assumptions:

Players are rational and care only about own material payoff.
Public good is non-excludable and non-rivalrous.
Prediction:

Each player contributes £0 (free-riding).
Maximises individual payoff regardless of others’ contributions.
Social Optimum vs Self-Interest:

If all contribute £10:
Total = £40 → Multiplied = £120 → Each gets £30
If one free-rides:
Total = £30 → Multiplied = £90 → Each gets £22.50
Free-rider keeps £10 → Total = £32.50
Implication:

Incentive to free ride undermines cooperation.

Question 20

What are the standard findings from the Public Good Game?

Answer 20

mpirical Findings:

In one-shot games, average contribution ≈ 50% of endowment.
In repeated games, contributions decline over time, often approaching 0%.
Interpretation:

Initial cooperation exists, but conditional cooperation breaks down if others defect.
Players are willing to cooperate, but only if others do too.
Your Notes (Slide 23):

If everyone contributes in early rounds, group morale stays high.
If someone defects, others retaliate by reducing their own contributions.

Question 21

What variations affect behaviour in the Public Good Game?

Answer 21

Key Variations:

Group Size (n):
Larger groups → lower contributions (diffusion of responsibility).
Multiplier (r):
Higher r → higher contributions (greater return on cooperation).
Contribution Type:
Continuous (e.g. £0–£10) → more cooperation
Binary (all or nothing) → less cooperation
Risky Returns:
Mixed results; uncertainty can reduce cooperation.
Punishment Mechanisms:
Ability to punish free-riders → increases cooperation significantly.

Question 22

Models explaining other-regarding preferences

Answer 22

To reconcile experimental findings that contradict the self-interest hypothesis, several models have been developed:

Models of Social Preferences

Utility depends not only on own material payoff but also on the allocation of resources within a reference group.
Captures altruism, envy, and inequity aversion.
Models of Interdependent Preferences

Preferences depend on the type of the agent one is interacting with.
E.g., altruistic with altruists, selfish with selfish types.
Models of Intention-Based Reciprocity

Preferences depend on beliefs about the intentions of others.
Unlike types (which are fixed), intentions can vary.
Axiomatic Approaches

Segal & Sobel (2004): derive fairness and reciprocity from axioms.
These models are psychologically plausible but often lack formal axiomatic foundations.
No conclusive “winner” among models, but Fehr & Schmidt (2006) provide a key discussion.

Question 23

What are social preferences and how do they differ from self-interest?

Answer 23

Question 24

Fehr & Schmidt model of inequity aversion

Answer 24

Question 25

Meaning of α and β in inequity aversion

Answer 25

Question 26

What are the alternative explanations for other-regarding behaviour beyond social preference models?

Answer 26

Beyond formal models, several psychological and social mechanisms explain prosocial behaviour: 1. Warm Glow Giving Andreoni (1990): People give because it feels good. Known as “impure altruism”. Example: “Feel good about yourself – Give blood” (American Red Cross). If utility depended only on outcomes, government provision would crowd out private giving — but it doesn’t. 2. Social Norms People give because of social expectations. Descriptive norms: What people do (e.g., “People are generous”). Signal appropriateness of action. Vesterlund (2003), Bohnet & Zeckhauser (2004) (UG), Shang & Croson (2009) (public radio fundraising). Injunctive norms: What people ought to do (e.g., “You should be generous”). Noncompliance leads to social disapproval. Bernheim (1994), Raihani & McAuliffe (2014) (DG). 3. Image Concerns Two components: Self-image: How I see myself. Social image: How others see me. People act fairly to maintain a positive self-concept. When they can avoid responsibility (e.g., via uncertainty), they may act selfishly.

Question 27

Moral wiggle room: Dana, Weber and Kuang (2007) findings

Answer 27

Dana, Weber & Kuang (2007): Study on illusory preference for fairness using a binary dictator game. Experimental Conditions: Baseline (Full Info): Dictators know the exact payoffs. Hidden Info Treatment: Dictators are told there’s a 50/50 chance of two payoff matrices but can choose to reveal which one applies. Key Findings: Under full information, only 26% choose the unfair option. Under uncertainty, 72% choose the unfair option. In hypothetical scenarios: 0% choose unfair under full info. 41% still choose unfair under uncertainty. 50% of participants choose to reveal the matrix. Among those who revealed and saw misaligned payoffs: Only 25% chose the unfair option. Among those who did not reveal: 100% chose the selfish option. If revealed matrix showed aligned payoffs, only 10% chose the unfair option. Those under uncertainty: 67% chose selfishly. Interpretation: People use uncertainty as an excuse to act selfishly. Those who seek information are more likely to act fairly. Suggests that image maintenance (not fairness per se) drives behaviour. User Notes: Participants who clicked the reveal button wanted to ensure the other player was okay — they didn’t exploit the moral wiggle room. Those who didn’t reveal used plausible deniability to justify selfishness.

Question 28

Limitations of Dana et al. (2007) moral wiggle room study

Answer 28

Dana, Weber & Kuang (2007) conducted influential experiments on moral wiggle room, but several limitations and follow-up studies are important to understand: 1. Small Sample Size The original study had a limited number of participants, which may affect generalisability. 2. Self-Selection into Information A key concern: Is it the lack of information that causes selfish behaviour? Or do pro-social individuals choose to reveal information because they care more? 3. Sorting Hypothesis Generous people may actively seek information to ensure fairness. Selfish individuals may avoid information to maintain plausible deniability. 4. Replication and Extensions Larson & Capra (2009) replicated the effect, supporting its robustness. Conrads & Irlenbusch (2013) and Grossman & Van der Weele (2017) explored the sorting mechanism. Arroyos-Calvera, McDonald, Read & Rigal (2020) provided causal evidence: Participants expressed their information preferences. But were randomly assigned to information conditions. This design helps isolate the causal effect of information availability on fairness. Conclusion: While the original findings are compelling, understanding the mechanisms behind information avoidance is crucial for interpreting the results.