Experimental Social Sciences: Investigating the Deep Bases of Economic and Political Decisions

1. Experimental Social Sciences: Investigating the Deep Bases of Economic and Political Decisions Akademi for Talentfulde Unge Alexander K. Koch & Michael Bang Petersen Aarhus, October2013

2. A Spotlight on Behavioral & Experimental Economics: Social Preferences Akademi for Talentfulde Unge Alexander K. Koch Aarhus, October 2013

3. Game 1 You have been provisionally allocated 100kr • Decide how to divide these 100kr between yourself and another randomly chosen person from this room • Use amounts divisible by 10kr. • Please write down how much you want to give to the other person • You keep the rest for yourself

4. Game 2 • You and another randomly chosen person from this course have to split 100kr. • The procedure is as follows: • Stage 1: you (the sender) propose how to divide these 100kr between yourself and the other person • Stage 2: the other person (the receiver) can accept or reject • If the receiver rejects: you both get 0kr. • If the receiver accepts: the 100kr. are shared as proposed in stage 1 • Which division would you propose as sender (use multiples of 10kr.)? • Suppose now you are the receiver.What is the lowest offer from the sender that you would accept?

5. From homo oeconomicus to homo sapiens • Prototypical economist conception of human behavior: • People maximize their (discounted, expected) utility • People are governed by self-interest • People are fully rational, i.e., decisions result from a fully rational process of finding an optimal choice given the constraints and all information available Experimental economics:tests of economic models in the laboratory/field have shown that some basic postulates in economic theory should be modified Behavioral Economics

6. What is behavioraleconomics • Behavioral Economics increases the explanatory power of economics by providing it with more realistic psychological foundations • Keep using the same powerful analytical end empirical tools but modify assumptions from standard economic theory: • Examples: • Realistic utility functions: social preferences, reference dependent preferences • Unstable preferences: e.g. why do people make forever resolutions to go on e.g. a diet or stop smoking, only to give in later • Biases, mistakes • Boundedrationality

7. Social preferences • Why do wedonatemoney? • Why do wecareaboutwhatothers have? • Why do wecareabouthowothersseeus?

8. Game 1: Dictator Game Decide how much of 100kr. to give to a random person • Whatwould the standard economicmodel predict? • What decisions do youactuallyexpect? • Whatmotivatedyour decision?

9. Game 1: Dictator Game • The standard economic model predicts that you keep all of the 100kr. for yourself • Experimental results (e.g. Andreoni and Miller 2002): • 40 percent of senders keep everything for themselves • 20 percent give more than 0, but less than 50 percent to the other person • 40 percent divide the amount of money equally • Almost nobody gives more than 50 percent • Behavior is quite sensitive to context • Anonymity (also vis-a-vis experimenter) • Framing: 'Wall Street Game' vs. 'Community Game'. • Small changes in protocol: choice set included option to take money, moral wriggle room

10. Game 2: Ultimatum Game • Split of 100kr. • If the receiver rejects sender’s offer, both get 0kr. • If the receiver accepts: 100kr. shared as proposed • Whatwould the standard economicmodel predict? • What decisions do youactuallyexpect? • Whatmotivatedyour decision?

11. Game 2: Ultimatum Game • The standard economic model predicts that you propose to keep the 100kr. for yourself and that the other person accepts • Numerous experimental studies from different countries, with differentstakesizes and differentexperimentalprocedures, clearly refute the prediction of the standard model • There are virtually no offers above 0.5 • The vast majority of offers in almost any study is in the interval [0.4; 0.5] • There are almost no offers below 0.2 • Low offers are frequently rejected, and the probability of rejection tends to decrease with the share offered

12. Public good game (social dilemma) • You and 3 other people from this class form a group. • Each of you can contribute to a public good • You are each given 200kr. • Your task is to decide how much to keep for yourself and how much to contribute to the public good • Your payoff depends on how much you and the others invest in the public good / keep for themselves as follows: • Your payoff= 200 - (your contribution to the PG)+ 0.4 x (sum of contributions of the 4 participants)

13. Predictions • The standard economic model predicts that everybody • contributes0 to the public good • What would be the socially efficient outcome? • Compare to the prisoners’ dilemma!

14. Experimental results • In the lab, subjects play this game ten times in a row (with the same group members or with different group members) • In the first rounds, some subjects contribute a positive amount • The contribution rates are declining • In the final period, the vast majority of subjects (on average 73%) play the equilibrium strategy of complete free riding (contributenothing) • So what about our social preferences now?

15. A variation: PG game with punishment • Suppose now that after deciding how much to contribute to the public good and learning how much each member contributed, group members can punish each other by assigning “punishment points" • Punishing other participants reduces their income, but it also reduces the income of the person who punishes • Standard economictheory: nopunishment • Let us consider the second stage (punishment stage) first (backward induction) • Suppose somebody contributed 0 and you contributed 20. Should you punishhim? • No, because you cannot change his contribution anymore! Punishing him reduces however your own income! • Thus, we should observe no punishment in the last stage • But then, what should people contribute in the first stage?

16. Experimental results Fehr and Gachter (2000)

17. Experimental results • People punishfree riders: • The vast majority of punishments are imposed by cooperators on the free-riders • Lower contribution levels are associated with higher received punishments • Consequence for cooperation: • Defectors do not gain from free riding because they are being punished • A strikingly large fraction of roughly 80 percent cooperates fully in the game with punishment in the final period • So what about the standard theory again? How can we reconcilethesepuzzling facts?

18. Summary • In some cases the standard model works quite well and social preferences seem not to matter (market experiments, public good games) • But we have also some examples where the standard model does not make the right prediction and social preferences seem to matter (dictator game, ultimatum game, public good game with punishment) • Is there a simple common principle that can explain the evidence? • Note: We do not want to have a model that explains one example, but not the others

19. Social preferences • Key idea: a player’s utility does not only depend on his own payoff, but also on the payoff of the other player • Altruism(Andreoni and Miller 2000): • A person is altruistic if her utility increases with the well being of other people • Can explain behavior of some (but not all) people in the dictator game • Can't explain behavior in ultimatum game • Inequity aversion(Fehr and Schmidt 1999, Bolton and Ockenfels2000): • A person is altruistic towards other players if their material payoffs are below an equitable benchmark, but she feels envy when the other players' material payoffs exceed this level • For most economic experiments it seems natural to assume that an equitable allocation is an equal monetary payoff for all players

20. Summary • Inequality aversion model canexplain: • Positive and negative actions towards other players • Behavior in market, dictator, ultimatum, public and public good with punishment games (and others not metioned) • Why fairness plays a smaller role in most markets for goods (no playe alone can enforce equitable outcome) than in labor markets • Problems: • Consider again the ultimatum game, but now suppose a computer randomly chooses for the sender • Suppose the computer proposes 10kr to you (i.e., the other player would get 90kr). Would you accept or reject? • What if a real person proposes 10kr to you? • Inequity aversion predicts there is no difference between these two scenarios • However many people would accept the offer if came from a computer but not if another person proposed it • Why? Intentions matter!

21. Which boss would you prefer to negotiate with over your salary?

22. The deep bases of behavior… • Ourpreferencesareshaped by evolution • our ancestors were successful at reproducing • suppose that we have inherited our ancestors’ preferences (genetically, culturally) • then our preferences should direct us towards maximization of reproductive success • Individual selection theory suggests a world populated by resolutely selfish “homo economicus” • Group selection theory: groups with internal cooperation will be more successful than other groups, and that this may cause altruistic behaviors or individual sacrifices for the common good of the group to survive and in some circumstances thrive • We have ”biases” shaped by evolution • Preferences can explain why some behavior is “rational” • But some facets of behavior seem “hard wired” rather than a rational response

23. The deep bases of behavior… • Ourpreferencesareshaped by evolution • our ancestors were successful at reproducing • suppose that we have inherited our ancestors’ preferences (genetically, culturally) • then our preferences should direct us towards maximization of reproductive success • Individual selection theory suggests a world populated by resolutely selfish “homo economicus” • Group selection theory: groups with internal cooperation will be more successful than other groups, and that this may cause altruistic behaviors or individual sacrifices for the common good of the group to survive and in some circumstances thrive • We have ”biases” shaped by evolution • Preferences can explain why some behavior is “rational” • But some facets of behavior seem “hard wired” rather than a rational response

25. Raise your hand if you heard…

26. Raise your hand if you heard…

27. McGurkeffect • Interaction between hearing and vision in speech perception • The visual information we gets from seeing a person speak changes the way we think we hear the sound • Vision: very accurate • Hearing: not so accurate • Evolution has taught us to discriminate between low and high quality signals: • If vision signal present, trust it more than auditory signal

28. Are we still influenced by howwesolvedpre-historic decisions? • Imagine you are a pre-historic caveman, who has just killed a big animal • On the horizon you spot a man who sets off in your direction • Should you flee or should you riskconfront him in a physical fight? • Models of behavior in resource conflicts suggest that adaptive strategies depend on asymmetries in fighting ability • When own relative fighting ability is high (and correctly assessed), it is adaptive to escalate the conflict • For humans, one key component of fighting ability is upper-body strength

29. Do prehistorictraitsstill (unconsciously) influenceourbehavior? • Experiment: • Are peopleable to assessphysicalstrength from minimal cues? • Do theybargaindifferently with stronger opponents? • Setup: • Measure strenght in one sample thatplays2nd mover (receiver) role in ultimatum game • Have another sample rate strenghtand play 1st mover (sender) role in ultimatum game

30. The rated • Aarhus Universitycanteen: • 100 male subjects • Photographed • Took several physical measures: Grip strength, flexed biceps, chest, • waist • Procedure took2-3min, coffee voucher for participation • Online survey: • 50 subjects from canteen experiment participated • 2nd decisions in trust and ultimatum game • UG: subject states minimum amount [0,1000] he would accept • TG: strategy method; the subject states for each amount • (0,100,200,300,400) the sender might send how much he would send back • One participant and one game was randomly selected, matched with a first mover (a subject from Aalborg) and paid • Short questionnaire: Self-assessed strength and attractiveness

31. The raters • Online survey with Aalborg University students: • Participants: 548 full participants (125 partial responses) • Pictures: Each person was confronted five blurred and five clear pictures • Decisions and questions for eachphoto: • Rate strength and attractiveness on 5-point scale • Play the ultimatum and trust game as a 1st mover against pictured subject • Self-rated strength and attractiveness • Severalsurvey questions (e.g. fighting history) • One subject and one decision was randomlyselected for payment

32. People assessphysicalstrength from minimal cues Replication of Sell et al 2009: • Finding 1: There is a significant relationship between rated strength and actual strength • Regression of various strength measures (biceps, dynamometer, self-assessed strength) on strength estimates • β=0.13: +1 std.dev. strengthleadsto +0.13 std.dev. rating • No gender effects • Finding 2: the accuracy increases with the experience of seeing more pictures • Regression of order of pictures on strength estimates • Same effect size as Sell et al on pictures 4 & 5 (they have 59 pictures)

33. Accuracy is greater with similarstrength opponents • 1st step: Is accurate measure important? • Not if other way stronger or weaker • Yes, if opponent seems to have similar strength range; proceed then to 2nd step • 2nd step: get more precise estimateif deemed necessary Fights with similar people could potentially escalate • Finding 3: The more similar rater and rated think they are, the more precise the rater’s estimate • But, we do not find a similar effect for attractiveness precision (in line with formidability hypothesis)

34. Webargaindifferently with strongeropponents • 1st mover (sender) decisions in the UG: • Finding 4: The stronger the person (in rater's mind), the higher the offer • The more attractive the person, the higher the offer • If we consider strength and attractiveness together, then both have a significant effect on the offer • Average offer: 454 • one unit higher strength rating: + 6 • i.e. below average -> above average: + 18 (4 percent higher offer) • one unit higher attractiveness rating: + 14

35. Conclusions • Humansaredeply social creatures • Wecareaboutothers’ wellbeing and others’ intentions • Ourstrategiesrelyon (rational) consideration of our • social preferences • howotherswillrespond to ourbehavior • Ourestimates of howotherswillresponddependpartially on (hard-wired) strategiesshaped by ancientevolutionaryenvironment