Ph.D. in Economics 2011-2012 University of Siena Course Decision Theory INDIVIDUAL CHOICE BEHAVIOR...

Ph.D. in Economics 2011-2012University of Siena

Course Decision Theory

INDIVIDUAL CHOICE BEHAVIOR IN THE LABORATORY

Alessandro Innocenti [email protected]

Outline

• LABORATORY METHODS • CONCEPTIONS OF RATIONALITY • CHOICE ANOMALIES • COGNITIVE ECONOMICS

• NEUROECONOMICS

• VIRTUAL EXPERIMENTS

• BEHAVIORAL DECISION-MAKING

1

Main references

D. Friedman, S. Sunder, Experimental methods. A primer for economists, Cambridge: Cambridge University Press, 1994

G. Loewenstein, S. Rick, J. D. Cohen, Neuroeconomics, Annual Review of Psychology, 2008, 59:647–72

Other references

Berg, Joyce, Dickhaut John and McCabe, Kevin, Trust, Reciprocity, and Social History Games and Economic Behavior, 1995.

Camerer, Colin - Loewenstein, George “Behavioral Economics: Past, Present and Future”, 2002.

Camerer, Colin - Loewenstein, George- Prelec, Drazen, “Neuroeconomics: How Neuroeconomics can inform economics”, Journal of Economic Literature 2005.

Camerer, Colin F. Behavioral Game Theory. Experiments in Strategic Interaction, New York and Princeton University Press, Princeton, 2003.

Davis, Douglas D. - Holt, Charles A. Experimental Economics, Princeton University Press, Princeton, 1993.

2

Friedman, Daniel - Cassar, Alessandra. Economics Lab. An intensive course in experimental economics, Routledge, London and New York, 2004.

Innocenti Alessandro, Lattarulo, Patrizia, Pazienza Maria Grazia, "Heuristics and Biases in Travel Mode Choice", 2009.

Jones, Martin – Sudgen, Robert. “Positive confirmation bias in the acquisition of information”,Theory and Decision, 50, 2001, 59-99

Kagel, John H. - Roth, Alvin E. The Handbook of Experimental Economics, Princeton University Press, Princeton, 1997.

Kahneman, Daniel - Tversky, Amos. “Prospect Theory: An Analysis of Decision under Risk”, Econometrica, 47, 1979, 263- 91

Kosfeld, Michael, Markus Heinrichs, Paul J. Zak, Urs Fischbacher & Ernst Fehr “Oxytocin increases trust in humans“ Nature 2005

Kuhnen Camelia M., Knutson, Brian “The Neural Basis of Financial Risk taking “ Neuron 2005

McCabe, Kevin, Daniel Houser, Lee Ryan, Vernon Smith, and Theodore Trouard. ”A functional imaging study of cooperation in two-person reciprocal exchange” Proc. Nat. Ac. Sci. USA 2001

Smith, Vernon. “Economics in the Laboratory”, Journal of Economic Perspectives, 8, 1994, 113-131.

3

Laboratory methods

POINTS OF VIEW

PROS

“Would it not be better to leave laboratory experiments to psychologists who are trained to run them properly? Nobody doubts that we have a great deal to learn from psychologists about laboratory technique and learning theory, but recent history would nevertheless suggest that the answer is a resounding no. Our comparative advantage as economists is that we not only understand the formal statements of economic theory, but we are also sensitive to the economic environments and institutions within which the assumptions from which such statements are deduced are likely to be valid. Just as chemists know not to mix reagents in dirty test tubes, so we know that there is no point in testing economic propositions in circumstances to which they should not reasonably be expected to apply.”

(Binmore 1999)

“Once models, as opposed to economies, became the focus of research the simplicity of an experiment and perhaps even the absence of features of more complicated economies became an asset. The experiment should be judged by the lessons it teaches about theory and not by its similarity with what nature might happen to have created.”

(Plott 1991)

4

Laboratory methods

POINTS OF VIEW

CONS

The laboratory is not a socially neutral context, but is itself an institution with its own formal or informal, explicit or tacit, rulesHuman agency takes place within a socio-economic world that is structured in the sense that it consists of internally-related positions and systemsExperimentation in economics is likely to be of limited value, save for situations – such as auctions – that exist in conditions of relative isolation and are characterized by low internal complexity

(Siakantaris 2000)

1. experimental situations often project a game-like atmosphere in which a ‘subject’ may

see himself as ‘matching wits’ against the experimenter2. experimental subjects are cast in roles and they can act in accordance with his

(mis)perceptions of these roles3. experiments have too short horizons (real world lasts many years and many trials)4. human beings are capable to control their behavior through the implementation of

abstract rules(Cross 1994)

5

6

DATA SOURCES

HOW? WHERE?

Happenstance

(uncontrolled conditions - ongoing processes)

Experimental (controlled conditions - deliberately created)

Field

(naturally occurring environment)

National Accounts Commodity Prices

Income Maintenance Experiments

Field Experiments

Laboratory

(artificial environment)

Casual Processes in the Lab Discovery of Penicillin

Choice Experiments Auctions Simulation

Laboratory Asset Markets

EXPERIMENTAL ECONOMICS LABORATORY + EXPERIMENTS (artificial environment) + (controlled ad hoc conditions)

PURPOSES OF EXPERIMENTS (WHY?)

1) Test of Behavioral Hypotheses. by constructing a laboratory environment that satisfies as many of the structural assumptions of a particular theory, it is possible to verify its behavioral implications

2) Theory Stress Tests

to examine the sensitivity of a theory to violations of obviously unrealistic assumptions

3) Searching for Empirical Regularities

heuristic experiments to discover and document stylized facts

(Davis-Holt, Experimental Economics 1994)

a) Speaking to Theorists

b) Searching for Facts

c) Whispering in the Ears of Princes(Roth 1986)

7

EXPERIMENTAL METHODOLOGY (HOW?)

1. PROCEDURAL REGULARITYto permit replications that the researcher and observers would accept as being valid

- instructions- subject pool and methods of recruiting subjects- experimental physical environment- computerized or manual

2. MOTIVATION- Induced-value theory: use of a reward medium allows to induce pre-specified

characteristics in experimental subjects and to make subjects’ innate characteristics largely irrelevant

- monotonicity: subjects prefer more reward medium to less and not become satiated

- salience: rewards are explicitly and unambiguously connected to the decisions made

- dominance: changes in subjects’ utility from the experiment come mainly from the reward medium and other subjective costs or benefits are rendered negligible by comparison, i.e. others’ reward

8

3. UNBIASEDNESS

Experiments should be conducted in a manner that does not lead participants to perceive any particular behavioral pattern as being correct or expected, unless explicit suggestion is a treatment variable - double blind setting

4. CALIBRATION

The design has to pre-specify and to cleanly separate the experimental predictions of alternative theories.

5. DESIGN PARALLELISM

Results established in the lab hold in other, especially non-lab, real-world situations where similar ceteris paribus conditions hold

Vernon Smith’s parallelism precept (1982): “Propositions about the behavior of individuals and the performance of institutions that have been tested in laboratory microeconomics apply also to non-laboratory micro economies where similar ceteris paribus conditions hold”

Charles Plott (1982): “While laboratory processes are simple in comparison to naturally

occurring processes, they are real processes in the sense that real people participate for real and substantial profits and follow real rules in doing so. It is precisely because they are real they are interesting”

9

PROFESSIONAL SUBJECTS, STUDENTS or WHAT?

Main Subjects pool - Undergraduate students

readily accessible low opportunity costs steep learning curve they do not know much about experimenter’s hypothesis

PhD students

unreliable subjects because they get interested in what are you doing and respond to their understanding of your topic rather than to incentives you have constructed

Classes or friends

dominance or salience at risk, conflicts between personal, teaching and scientific aims

10

Professional subjects comparisons show that students are more adept at maximizing their profits and

learning in the lab high opportunity costs pre-specified and innate characteristics are too strong when involved in laboratory markets they attempt to apply rules of thumb, which,

valuable for dealing with uncertainty in the parallel natural market, are meaningless guides in the lab.

Controversial evidence

Burns (1985): professional wool buyers and students in a progressive auction (professionals apply familiar rules and not adjust to design requirements)

Dyer, Kagel, and Levin (1985): bidding behavior of students and construction workers (no difference)

Dejong et al (1988): Businessmen and students in sealed-offer markets (same profits, but higher variance for businessmen)

What about gender, age, risk attitude, experience?

11

Kagel, John H. - Roth, Alvin E.

The Handbook of Experimental Economics

Princeton University Press

INDEX

a) public goods

cooperation vs. selfishness (social dilemmas, free-riding, institutions)

what improves cooperation (thresholds, learning)

b) coordination problems

experiments with overlapping generations

coordination games with Pareto ranked equilibria

decentralized matching environments

c) bargaining experiments

agreements

causes of disagreements and costly delays

bargaining protocol and preplay communications

13

d) industrial organization

trading institutions centralized and decentralized

monopoly regulation and potential entry

market structure and market power

collusion factors

product differentiation and multiple markets

e) experimental asset markets

informational efficiency of markets

state-contingent claims and bubbles

learning and dynamics of adjustment paths

investment and public policy

f) auctions

symmetric independent private-values models

common value auctions

collusion

g) individual choice behavior

14

INDIVIDUAL CHOICE BEHAVIOR

I. JUDGMENT

A. Calibration

1. Scoring Rules

2. Confidence Intervals

B. Perception and Memory Biases

C. Bayesian Updating and Representativeness

1. Underweighting on Likelihood Information (Conservatism)

2. The Law of Small Numbers and Misperceptions of Randomness

D. Confirmation Bias and Obstacles to Learning

E. Expectations Formation

F. Iterated Expectations and the Curse of Knowledge

1. False Consensus and Hindsight Bias

2. Curse of Knowledge

G. The Illusion of Control

15

II. CHOICE UNDER RISK AND UNCERTAINTY

A. Mounting Evidence of Expected Utility Violation (1965-1986)

1. The Allais Paradoxes

2. Process Violations

3. Prospect Theory

4. Elicitation Biases

B. Generalizations of Expected Utility and Recent Tests

1. Predictions of Generalized EU Theories

2. Empirical Studies Using Pair-wise Choices

3. Empirical Studies Measuring Indifference Curves

4. Empirical Studies Fitting Functions to Individuals

5. Cross-Species Robustness: Experiments with Animals

C. Subjective Expected Utility

1. The Ellsberg Paradox

2. Conceptions of Ambiguity

D. Choice over Time

16

II. CHOICE UNDER RISK AND UNCERTAINTY / II

E. Description Invariance

1. Framing Effects

2. Lottery Correlation, Regret, and Display Effects

3. Compound Lottery Reduction

F. Procedure Invariance

1. New Evidence of Preference Reversal

2. Arbitrage and Incentives

3. Reversals and Markets

4. Social Comparisons and Reversals

G. Endowment Effects and Buying-Selling Price Gaps

1. Market Experiments

2. Endowment Effects: Some Psychology and Implications

K. Search

1. Search for Wages and Prices

2. Search for Information

17

BIASES IN JUDGMENT

“People rely on heuristic principles which reduce the complex tasks of assessing probabilities and predicting values to simpler judgmental operations. In general, these heuristics are quite useful, but sometimes they lead to severe and systematic errors”

(Tversky and Kahneman 1974)

CONFIRMATION BIAS

Once individuals devise a strong hypothesis they will tend to misinterpret or even misread new information unfavorable to this hypothesis

Also production of treatment effects: when a researcher believes an hypothesis is true, he often produces a biased sample of evidence that reinforces his or her belief (unconsciously?)

Consequence is obvious: confirmation bias inhibit learning whether one’s underlying belief is false

But fresh thinkers may be better at seeing solutions to problems than people who have meditated at length on the problems, because the fresh thinkers are not overwhelmed by the “interference” of old hypotheses.

18

Correlated phenomena

FALSE CONSENSUS

People use their own tastes and beliefs as information in guessing what others like and believe

Application: to put in other people’s shoes is not useful to find focal points

HINDSIGHT BIAS

Current recollections of past judgments tend to be biased by what actually happened since then

Application: adaptive expectations vs. rational expectations

19

AN ILLUSTRATIVE EXPERIMENT

Martin Jones and Robert Sugden “Positive confirmation bias in the acquisition of information”,Theory and Decision, 50, 2001, 59-99

Positive confirmation bias: tendency, when testing an existing belief, to search for evidence which could confirm that belief, rather than for evidence which could disconfirm it

Wason’s (1968) selection task

Four double-sided cards. Subjects are told that each card has a letter on one side and a number on the other, but they can see only the upper faces of the four cards

Four cards uncovered show ‘A’, ‘D’, ‘4’ and ‘7’

Each subject is asked to consider the following rule, as applied to the four cards: ‘If a card has a vowel on one side, then it has an even number on the other side’

Instruction: ‘Your task is to say which of the cards you need to turn over to find out whether the rule is true or false’

20

Two most common responses ‘A’ card alone ‘A’ and ‘4’ cards in combination

The correct answer to the question posed is, of course, the combination of ‘A’ and ‘7’.

The frequently-chosen ‘4’ card can provide no information which is relevant to the issue of whether the rule is true or false

The ‘A’ and ‘4’ cards are the ones that are capable of providing evidence which confirms the rule: by turning over either of these cards, the subject may find a card with a vowel on one side and an even number on the other

In contrast, the ‘7’ card can only disconfirm the rule (i.e. by revealing a card which has a vowel on one side but not an even number on the other)

In this sense, the evidence from the selection task can be interpreted as consistent with positive confirmation bias

21

Criticism

The original selection task was formulated in highly abstract terms

Counterargument

Correct response might be facilitated by adding thematic content to the task, i.e. by providing a cover story which accounts for the statement and gives some point to the selection task

Jones and Sudgen’s design

Subjects have to pay a fixed cost per card turned over

After they have made this choice, the chosen cards are turned over

Then they make the judgment that the statement is ‘true’ or ‘false’

Finally the remaining cards are turned over and they receive a fixed reward if and only if their judgment was in fact correct

22

Experiment carried out at the University of East Anglia in Norwich 120 students recruited on the campus (wide range of courses) Computerized experiment No communication between subjects

Each task is presented by means of a sequence of six screens

The screen presents first the cover story, then the statement and finally four cards to choose

Each object has two characteristics, each of which can take one of two values that correspond with p, p, q, and q (as before vowel and consonant, even and odd)

Each subject perform seven different tasks

<p, q> or < q, p>, if turned over, is a disconfirmation of the experimental HP

<p> <p, q> and <q, p> are confirmations

23

Exemplificative Tasks

1. Relatives . A survey is taken of 100 people in Los Angeles, Seattle, London and Norwich who have relatives living in other cities. Each person in the survey living in Britain has relatives in Los Angeles or Seattle and each person living in America has relatives in Norwich or London. No one has relatives in more than one city. The details of the survey are written down on report cards by putting the city each person lives in on one side of the card and the city their relatives live in on the other side. A sample of four report cards is selected. Look at whichever cards you wish to test the statement:

[Standard statement] Every person in the sample who lives in London also has a relative who lives in Los Angeles.

[Contraposed statement] Every person in the sample who lives in Seattle also has a relative who lives in Norwich.

2. Drinkers . Only people over the age of eighteen are allowed to drink alcohol in a pub in Britain. A survey is carried out of 100 people in a large public house which identifies their age and whether they are drinking alcohol or a soft drink. Each person’s details are put down on a report card with the person’s age on one side and their drinking behaviour on the other. A sample of four report cards is selected. To find out if the four people in the sample are obeying the law, look at whichever cards you wish to test the statement:

[Standard statement] Every person in the sample who is drinking alcohol is also over eighteen.

[Contraposed statement] Every person in the sample who is under eighteen is also drinking a soft drink.

24

Results

In favour of the confirming bias hypothesis: 62% of the choices (445/720)

<No cards> 18%

<p> 14%

<p, q> 18%

Conclusions

Overwhelming evidence that subjects’ information-gathering decisions are systematically biased in favor of

information which is potentially confirming

But behavior seems to have been closer to Bayesian rationality than in many other selection task experiments

Especially the drinkers story facilitates Bayesian rationality (why?)

What is the effect of financial incentives?

Application to economic learning: an agent who repeatedly faces the same set of options might retain the false belief that a particular option was optimal, even after long exposure to evidence which, rationally interpreted, would indicate the contrary

25

II. Conceptions of rationality

What do we mean by rational choice? Lots of formulations, involving assumptions of different strength

Different forms of rationality imply different experiments to test them

Goal oriented Satisficing behavior Maximizing behavior Ordinal utility maximization Expected utility maximization Subjective expected utility maximization

Experimental economics reveals the hidden or implicit assumption by showing anomalies in the formulation of rationality

Consequence: there is a variety of definitions of rational individual

And what about heterogeneity?

26

Risk neutral economic man: never buys insurance, but would be willing to pay any finite amount to participate in Petersburg paradox.

Expected utility maximizing man: buys insurance, but ignores sunk costs, and is immune to framing effects.

Almost rational economic man (e.g. prospect theory man) has malleable reference points and probability perceptions, but still has preferences - comfortable with non-utility Allais choices, but doesn’t exhibit preference reversals.

Psychological man doesn’t have preferences, has mental processes. Different frames and contexts, and different choice procedures elicit different processes - So he may sometimes exhibit preference reversals because choosing and pricing elicit different mental procedures.

Neurobiological man: doesn't (even) have a fixed collection of mental processes, in the sense of psychological man. He has biological and chemical processes which influence his behavior. Different blood chemistry leads to different mental processes; e.g. depending on the level of lithium (or Valium or Prozac) in his blood, he makes different decisions (on both routine matters and matters of great consequence - even life and death). An understanding of how chemistry interacts with mental processes has proved to be very useful, for instance in treating depression.

27

EXPERIMENTS WITHIN SUBJECTS

[Tversky and Kahneman 1981, Thaler 1980]

Experiment 1

(certainty effect)

Which of the following options do you prefer?

A. A sure win of $30 [78%] EV 30

B. An 80% chance to win $45 [22%] EV 36

Which of the following options do you prefer?

C. A 25% chance to win $30 [42%] EV 7.5

D. A 20% chance to win $45 [58%] EV 9

0,20×U(45) > 0,25×U(30) U(45 )/U(30) > 0,25/0,20

0,80×U(45) < 1×U(30) U(45 )/U(30) < 1/0,80

but 0,25/0,20 = 1/0,80

28

Experiment 2

(loss aversion)

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. Sure gain of $240 [84%] EV +240

B. 25% chance to gain $1,000 and 75% chance to lose nothing [16%] EV +250

Decision (ii). Choose between

C. A sure loss of $750 [13%] EV -750

D. 75% chance to lose $1,000 and 25% chance to lose nothing [87%] EV -750

Experiment 3

(mental accounting)

Choose between

E. 25% chance to win $240 and 75% chance to lose $760 [0%] -510

F. 25% chance to win $250 and 75% chance to lose $750 [100%] -500

But E = A&D and F = B&C

29

Experiment 4 (shoes costs)

Imagine that you are about to purchase a jacket for ($125)[$15] and a calculator for ($15)[$125]. The calculator salesman informs you that the calculator you wish to buy is on sale for ($10)[$120] at the other branch of the store, a 20-minute drive away. Would you make the trip to the other store?Yes: 16% No: 84%

Experiment 5 (sunk costs)

Imagine that you have decided to see a play, admission to which is $10 per ticket. As you enter the theater you discover that you have lost a $10 bill. Would you still pay $10 for the ticket to the play?

Yes: 88% No: 12% Now imagine that you have decided to see a play and paid the admission price of $10 per ticket. As you enter the theater you discover that you have lost your ticket. The seat was not marked and the ticket cannot be recovered. Would you pay $10 for another ticket? Yes: 46% No: 54%

30

OTHER CHOICE ANOMALIES

BUYING-SELLING PRICE GAP

A simple class experiment

Half of you - randomly chosen - is named as “owners” and receive a windfall gift of a classy, stylish, desirable HBS pencil. You are asked to examine it closely. It is yours to keep, or to sell

The remaining half do not receive a pencil and is refereed to as “non-owners”

Then each owner is asked to pass his/her pencil to a neighboring non-owner, so that the non-owners can also fully examine the pencil.

It may exist some gains from trade. In order to assess this, the experimenter wants to elicit from each owner the minimum price at which he/she would be willing to sell the pencil and from each non-owner, the maximum price she/he would be willing to pay to buy the pencil.

Experimental finding: Owner prices (WTA) > Non-Owner prices (WTP)

Z

31

Economic theory predicts that the prices a person will pay to buy and sell an object should be the same.

Environmental economists in the 1970s first discovered that this is not true: duck hunters would pay $ 247 to maintain a wetland suitable for ducks but asked $ 1,044 to give up the wetland (Hammack J. and Brown G. M. Water fowl and wet lands: Toward bio economic analysis, John Hopkins University Press, 1974)

Students were willing to pay 2,75 on average for college mugs but they asked for 5,25 to sell their mugs (Kahneman, Knetsch, Thaler, “Experimental Tests of the Endowment Effect and the Coase Theorem,” JPE 1990)

EXPLANATIONS

Plott’s (1996) discovered preferences hp.: individuals may discover their valuations for unfamiliar items during the elicitation process

Economic factors: income effects and substitution, transaction costs, implied value of the good, profit motivation

Psychological factors: endowment effect, legitimacy, ambiguity and moral responsibility

32

ENDOWMENT EFFECT

People prefer the things they own, ceteris paribus (but what about the neighbor’s grass is always greener than yours?) Explanations- action error (Ritov-Baron 1991): fear of action errors is a bias in favour of inaction- higher sensitivity to overpaying (out-of-pocket costs) than to selling too cheaply

(opportunity costs) (Thaler 1980)- disposition effect (Weber-Camerer 1992): reluctance to take actions leading to

irreversible loss and eagerness to take actions creating gains (i.e. the volume of houses sold falls when housing prices fall )

- status quo bias (Samuelson-Zeckhauser 1988): if you have a current choice you enhance preferences for it

- prospect theory’s loss aversion (Tversky-Kahneman 1988): losses are more painful than equally sized gains are pleasurable

- action is different from giving advices: no endowment effect when people advise others (Marshall-Knetsch-Sinden 1988)

Consequence : Invalidates the Coase theorem, that is the valuation of a property right is

not independent of who owns the right – contracting parties allocate efficiently rights and duties if there is no transaction cost

33

CONSTRUCTIVE REACTIONS

(within standard economics)

34

Expected utility theory prospect theory

asymmetric response to price increases, downward-sloping labor supply among cab drivers

Exponential discounting

hyperbolic discounting addition and procrastination

Self-seeking behavior social utilities

trust and reciprocity in financial relationship

Equilibrium processes of equilibration drift effect, automata

ranked preferences constructed preferences

information manipulation in horse race betting, void informational cascades in the artistic markets

Bayesian probability judgments confirmation bias

Self-fulfilling expectations in financial markets, focal points

PROSPECT THEORYKahneman and Tversky Econometrica 1979

Experimental evidence a) people perceive the outcome of a monetary prospect in terms of the variations

(positive or negative) related to a non-constant reference level (usually the status quo) rather than in terms of absolute levels of wealth

b) people appear to be more adverse to losses, relatively to their reference level, than how they are attracted by the winning of the same value. The disutility of the monetary loss x is lower than the utility of winning the same amount x. Consequently, reaction to losses is stronger than the reaction to winnings.

Prospect Theory postulates the existence of two functions - the value function v - the weight function (or decisions weights) p - such as the decision maker strictly

prefers X a Y iff where xi = xi – x0 is the variation associated to a prospect xi with respect to a reference

point x0.

35

iiii yvqxvp

Differences between

prospect theory (PT) and subjective expected utility theory (SUET)

1) the decision maker is not interested in the final status per sé (SUET) but at the change of status ( xi) with regard to the reference point (x0) (PT)

2) the value function v is concave (“risk averse”) for gains and convex (“risk seeking”) for losses (PT).

3) the value function v is steeper around the reference point for losses than for gains (“loss aversion”).

4) the psychological sensitivity to losses and gains diminishes marginally: incremental winnings/losses give decreasing marginal utility/disutility

5) while in SUET the utility of any possible event is weighted with his probability, in PT the value of any welfare change is multiplied by a “decision weight”, that is not a probability but a probability transformation. Probability transformations do not follow probability rules and cannot be interpreted as degree of beliefs. They are obtained by choices and measure the impact of events on prospects’ desirability and not the perceived probability of events.

6) the weight function p is monotone, increasing, and discontinuous between 0 and 1, because it sistematically overweights very low probabilities and underweights medium and high probabilities (“certainty effect”)

36

Alternative theories to explain anomalies

Alternative conceptions of rationalityMachina’s (1989) non expected utility Gilboa and Schmeidler (2006) case based decision theory

Attempts to reconcile rational theory and irrationality in experiments Gode and Sunder’s (1993) zero intelligence agents in simulated experimental markets lead to nearly efficient outcomes (it does not take much rationality to behave nearly optimally in an experimental market )Cox and Grether (2005) endogenous “loss aversion” discovery of preference by watching others

Heuristic experiments : searching for new facts heterogeneous agents models: the abandonment of the fictitious construct of representative agent local network analysis – complex dynamic systems characterized by dispersed interaction among agents acting locally on each other in some space empirically-driven analysis à la Schellingcognitive economics and neuroeconomics

39

BEHAVIOURAL OR COGNITIVE ECONOMICS?

“Because economics is the science of how resources are allocated by individuals and by collective institutions like firms and markets, the psychology of individual behavior should underlie and inform economics, much as physics informs chemistry; archaeology informs anthropology; or neuroscience informs cognitive psychology. However, economists routinely—and proudly—use models that are grossly inconsistent with findings from psychology. A recent approach, ‘‘behavioral economics,’’ seeks to use psychology to inform economics, while maintaining the emphases on mathematical structure and explanation of field data that distinguish economics from other social sciences” (Camerer 1999)

Behavioural economics is a reunification of psychology and economics and it would preserve the distinctive emphasis on formal models and descriptive statistics that characterizes mainstream economics

Two key issues to deal with

1. the inconsistency of the predictions of most economic models with experimental results;

2. the rigidity of mathematical structure of that same models joined with the indefiniteness of the theoretical implications of the statistical data collected in the field

Z

40

Behavioural economics approach is a clear departure from the “as if” approach endorsed by Milton Friedman.

“F-twist” argument combines two criteria:

1. Theories should be judged by the accuracy of their predictions;

2. Theories should not be judged by the accuracy of their assumptions.

Because theories with patently false assumptions can make surprisingly accurate predictions, economic theories that assume that individual agents are highly rational and wilful, judge probabilities accurately, and maximize their own wealth might prove useful, even though psychology shows that those assumptions are systematically false.

The empirically-driven approach to behavioural economics agrees with criterion (1) and rejects criterion (2). Criterion 2 is rejected because of the primacy of criterion 1, based on the belief that replacing unrealistic assumptions with more psychologically realistic ones should lead to better predictions.

Behavioural economics emerges as the study of deviations from the paradigm of rational choice by relaxing the assumption of perfect rationality that pervades mainstream economics

Z

41

Cognitive economics is not a distinct subfield of economics but a school of thought based on the idea that the study of economic behaviour has to be founded on the interdisciplinary approach characterizing cognitive sciences

According to a well known definition, the field of Cognitive Science is formed by the intersection of a variety of different disciplines including cognitive psychology, philosophy of mind, linguistics, artificial intelligence and neuroscience

The research field of cognitive economics is the analysis of the mental and cognitive processes through which the economic agent collects, processes, interprets and uses information and knowledge to make economic choices.

Its main object is to open the black-box containing all the processes through which preferences are formed and are translated into choices.

Cognitive economics departs from behavioral economics, whose methodology is based on the analysis of the effectively exhibited behaviors, which is consonant with the axiom of revealed preferences which allows ignoring psychological determinantsof behaviour in economics

42

NEUROECONOMICS

Neuroeconomics is a sub-field of cognitive economics

Studies how the brain interacts with the environment to produce economic behavior

Neuroeconomics is the grounding of microeconomics in details of neural functioning.

While the revealed preferences approach has deliberately avoided trying to discover the neural determinant of choices, neuroscience is beginning to allow direct measurement of thoughts and feelings

Methodologically, neuroeconomics is not intended to test economic theory in a traditional way - particularly under the view that utilities and beliefs are only revealed by choices - but to establish the neural circuitry underlying economic decisions, for the eventual purpose of making better predictions.

43

BASIC PRINCIPLES

Much of the brain is constructed to support automatic processes which are faster than conscious deliberation and which occur with little or no awareness or feeling of effort

Economic behavior is under the pervasive and often unrecognized influence of finely tuned affective (emotion) systems that are localized in particular brain region

If affective systems are damaged or perturbed by brain damage, stress, imbalances in neurotransmitters, alcohol or “the heat of the moment” the deliberative system generally is not capable of getting the job done

Many behaviors that are clearly established to be caused by automatic or affective systems are interpreted by human subjects, spuriously, as the product of cognitive deliberation

The deliberative system, which is the system that is responsible for making sense of behavior, does not have perfect access to the output of the other systems, and exaggerates the importance of processes it understands when it attempts to make sense of the body’s behavior.

44

TOOLS

Animal studies

Human studies

Lesion studies (i.e., studies of patients with deficits that follow specific brain damage)

Single and multiunit recordings

Eyetracking

Measuring hormone levels

Galvanic skin response

Transcranial magnetic stimulation (TMS)

Imaging of brain activity

Electro-encephalogram (or EEG)

Positron emission topography (PET)

Functional magnetic resonance imaging (fMRI)

46

Brain imaging:

comparison of people performing different tasks (experimental + control task) by observing the images of the regions of the brain that are differentially activated by the experimental task.

Electro-encephalogram (or EEG) uses electrodes attached to the scalp to measure electrical activity synchronized to stimulus

events or behavioral responses known as Event Related Potentials, or ERPs

(poor spatial resolution but unobtrusiveness and portability)

Positron emission topography (PET) scanning measures blood flow in the brain, which is a reasonable proxy for neural activity, since neural activity in a region leads to increased blood flow to that region

(poor temporal resolution for stochastic lag of blood, i.e. flow)

Functional magnetic resonance imaging (fMRI), which tracks activity in the brain proxied by changes in blood oxygenation -

neural processes are thought to occur on a 0.1 millimeter scale in 100 microseconds (msec)

(the spatial and temporal resolution of a typical scanner is only 3 millimeters and about two seconds)

47

• Uses strong magnetic fields to create images of biological tissue– Measures hemodynamic

signals related to neural activity

• Blood Oxygenation Level Dependent (BOLD) contrast

• MR signal of blood is dependent on level of oxygenation

• Changes in deoxyhemoglobin

• Blood flow in the brain implies function– Studies have shown

regional brain activity when exposed to cues (Huettel et al. 2004)

Source: UC Irvine Center for Functional Onco-Imaging

Why is fMRI so exciting?

• Non-invasive• Better temporal

resolution• Good and

improving spatial resolution

• Can be used in conjunction with other methods (Savoy 2005)

Source: MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging Visiting Fellowship Program in fMRI, 2005

Basic facts about the brain

The brain is divided into two halves and each half is divided into four lobes: frontal, parietal, occipital and temporal

Regions of these lobes are interconnected and create specialized “circuits” for performing various tasks.

What do each of these lobes do?

Frontal Lobe - associated with reasoning, planning, parts of speech, movement, emotions, and problem solving

Parietal Lobe - associated with movement, orientation, recognition, perception of stimuli

Occipital Lobe - associated with visual processing

Temporal Lobe - associated with perception and recognition of auditory stimuli, memory, and speech

52

The human brain is a primate brain with more neocortex. The fact that many human and animal brain structures are shared means that human behavior generally involves interaction between “old” brain regions and more newly-evolved ones.

54

The “new” regions

Prefrontal cortex – the executive region because it draws inputs from almost all other regions and plan actions. The prefrontal area is the region that has grown the most in the course of human evolution and which, therefore, most sharply differentiates us from our closest primate relatives

The “old” regions

Limbic System as the main area involved with emotions Amygdala play an important role on the mediation and control of major affective

activities like friendship, love and affection, on the expression of mood and, mainly, on fear, rage and aggression. It is also the center for identification of danger

Hippocampus is particularly involved with memory phenomena, specially with the formation of long-term memory (the one that, sometimes, lasts forever).

Hypothalamus is involved in the so-called motivated behaviors, like thermal regulation, sexuality, combativeness, hunger and thirst. It is also believed to play a role in emotion.

55

Pons

Spinal Cord

Cerebellum

Amygdala

Thalamus

Hypothalamus

Hippocampal

FormationCorpusCallosu

m

Cingulate Gyrus

Striatum

Limbic System

Quadrant I - deliberate whether to refinance your house, poring over present-value calculations (is the realm of economics)

Quadrant II - used by “method actors” who imagine previous emotional experiences to fool audiences into thinking they are experiencing those emotions

Quadrant III - governs the movement of your hand Quadrant IV - makes you jump when somebody screws

58

Cognitive AffectiveControlled Processes serialeffortfulevoked deliberatelygood introspective access

I II

Automatic Processesparalleleffortlessreflexiveno introspective access

III IV

Controlled processes conscious and introspectively accessible tend to be serial and to use a step-by-step logic tend to be invoked deliberately by the agent when her or she encounters a challenge or surprise are often associated with a subjective feeling of effort

Automatic processes operate outside of conscious awareness tend to operate in parallel are often associated with a feeling of effort people often have surprisingly little introspective access to automatic choices Ex. a face is perceived as ‘attractive’, or a verbal remark as ‘sarcastic’, automatically and effortlessly

Cognitive processes those that answer true/false questions

Affective processes those that motivate approach/avoidance behavior. include emotions such as anger, sadness, and shame, as well as "biological affects" such as hunger, pain, and the sex

drive.

59

Automatic processes

Key principles

Parallelism much of the brain's processing involves processes that unfold in parallel and are not accessible to consciousness

Plasticity the brain undergoes physical changes as a result of these processes: when signals are repeatedly conveyed from one neuron to another, the connections between those neurons strengthen (Hebb 1949) . Information processing is unlikely to be reversible because the physiological processes that produce learning are themselves not reversible

Modularity it draws upon multiple modules specialized to perform specific functions neurons in different parts of the brain have different shapes, structures and functions

Specialization when the brain is confronted with a new problem it initially draws heavily on diverse modules, including, often, the prefrontal cortex, but over time, activity becomes more concentrated in modules that specialized in processing relevant to the task

60

Affective processes

Key Principles

Homeostasis Affective system involves detectors that monitor when a system departs from a 'set-point' and

mechanisms that restore equilibrium when such departures are detected (it is highly attuned to changes in stimuli rather than their levels). Some of these mechanisms do not involve deliberate action

Raw motivation Economists usually view behaviour as a search for pleasure . Neuroscience and other areas of psychology show that the motivation to take an action is not always closely tied to hedonic consequences ( liking vs. wanting systems)

Competition Affective system often plays as if the decision maker is of "two minds“. It drive us in one direction and

cognitive deliberations in another

Erroneous sense-making Since quadrant I often does not have conscious access to behavior in the other quadrants, it is often tends to over attribute behavior to itself, i.e. to a deliberative decision process.

61

CONSEQUENCES FOR ECONOMIC DECISION-MAKING

Economic decision making is not a unitary process—a simple matter of integrated and coherent utility maximization—because it is driven by the interaction between automatic and controlled processes.

The extent to which intertemporal choice is generated by multiple systems with conflicting priorities is consequently the most debated issue within neuroeconomics. Most evidence favors a multiple systems perspective.

Neuroeconomic research on social preferences is supportive of a dual-systems account, also with regard to how self-interest and fairness concerns interact to influence behavior

Economics is intertwined with o psychology by inspiring economic models increasingly grounded in psychological reality and by addressing debates on if multiple systems operate sequentially or in parallel to influence behavior

62

APPLICATIONS

The neural basis of financial risk-taking

Kuhnen & Knutson, The Neural Basis of Financial Risk Taking , Neuron 2005

Is individual investor deviation from optimal behavior due to emotion?Brain imaging evidence that anticipation of gains vs. losses activate different regions

Nucleus accumbens (NAcc) of ventral striatum =gains Anterior insula = loss

Examined whether anticipatory neural activity could predict optimal and suboptimal choices in financial choices Event related fMRI with 1.5T scanner 19 subjects (experts and non-experts)

Behavioral Investment Allocation Task (BIAS) ◦ 20 blocks 10 trials each◦ Randomly assigned one stock to be bad and other good (subjects do not know which)

Good stock (50% 10 dollari – 25% 0 dollari – 25% -10$ EV +2,5)

Bad stock (25% 10 dollari – 25% 0 dollari – 50% -10$ EV -2,5)

63

The top panels depict the contrast of large gains versus large losses during the Outcome period following stock choice. The bottom panels depict the contrast of chosen versus unchosen outcomes during the Market period following stock choice. n = 19.65

Findings

Nucleus accumbens activation • before choosing a stock• after a choice in which the gain is relatively higher

Anterior Insula activation • before choosing a bond• after a choice in which the gain is relatively lower

Interpretation distinct neural circuits linked to anticipatory affect promote different types of financial choices excessive activation of these circuits may lead to investing mistakes activation in the NAcc and anterior insula, respectively, index positive and negative anticipatory affective

states and that activating one of these two regions can lead to a shift in risk preferences.

Applications this explain why casinos surround their guests with rewardcues (e.g., inexpensive food, free liquor,

surprise gifts,potential jackpot prizes)—anticipation of rewards activates the NAcc, which may lead to an increase in thelikelihood of individuals switching from risk-averse to risk-seeking behavior.

A similar story in reverse may apply to the marketing strategies employed by insurance company

66

APPLICATIONS

Trust game and brain activation

Trust game (or investment game): Two players are paired off anonymously and respectively named as the sender and the responde The sender is given a certain amount of money and told that he or she can keep the entire amount or send

some or all of it to the responder. Any money passed from the sender to the responder is tripled by the experimenter and then given to the

responder. The responder can keep the entire amount or give back some or all of it to the sender. When the sender receives the amount sent back by the responder the game ends.

It measure of the propensities to trust, which is the proportion of the initial endowment sent by the sender, and to reciprocate, which is the ratio between the amount returned and the amount received by the responder.

Backward induction solution: the responder will not send any money back. anticipating the responder’s decision, the sender will not send any money to the responder.

67

Results from earlier experiments are inconsistent with the conventional game theory prediction.

68

Table 1. Experimental results on the trust game

Berg-Dickhaut-McCabe (1995)

Buchan-Croson-Johnson (2000)

Schwieren-Sutter (2003)

Burks - Carpenter -Verhoogen (2003)

Chaudhuri - Gangadharan

(2003)

Innocenti - Pazienza (2006)

No history

Social history

Only U.S.

All Single role

Both roles, no

prior

Both roles, prior

Double blind procedure

Double blind procedure

Trust

51.6 53.6 49 67 65.7 65.0 65.2 47.3 43.3 42.2

Reciprocity

30.1 40.2 22 37 37.6 43.6 25.9 17.1 17.5 16.2

Trust = Average fraction sent (Amount sent / Initial endowment); Reciprocity = Average fraction returned (Amount sent back/ Amount received)

70

Kevin McCabe, Daniel Houser, Lee Ryan, Vernon Smith, and Theodore Trouard ”A functional imaging study of cooperation in two-person reciprocal exchange” Proc. Nat. Ac. Sci. USA 2001 Design Subjects play the trust game both against a human opponent and against a computer program which, they were told, would play a human-like strategy.

Cooperation seems to be associated with the activation of the anterior paracingulate cortex, a brain region associated with interpreting and monitoring the mental state of others

Tool

Functional magnetic resonance imaging (fMRI)

Data analysis examines the bold response one TR (1.5 s) before the results screen, because decision making for cooperation is likely to be salient at this TR independent of the subject's position in the game

Subjects are likely to ask themselves during this wait condition, "What is my counterpart doing?" and begin

to form beliefs about what a delay means about their counterpart's desires.

Expectations

Human and computer treatments to generate differential activations associated with predicting and understanding the cooperative intentions of another human. Our analysis treats the rolling-bars condition as the baseline.

71

Findings

McCabe at al found that subjects were more likely to cooperate with real humans than with computers and that cooperators have a significantly different brain activation in the two conditions

The six subjects with the highest cooperation scores show significant increases in activation in medial prefrontal regions during human-human interactions when compared with human-computer interactions.

The six subjects who received the lowest cooperation scores (22, 10, 18, 21, 11, and 3) did not show significant activation differences in medial prefrontal cortex between the human and computer conditions.

72

73

Bold response of a cooperator for the contrast human (H).computer .The blobs on the glass brain are clusters of at least 12 contiguous voxels that show significantly moreactivation in the human than computer condition. The cursor on the glass brain is located at the voxel with the greatest t statistic within the medial prefrontal clusters. The graph immediately below the glass brains displays the peristimulus time histogram at the voxel indicated by the cursor. This is the mean of the adjusted (for time and physiological effects) response to the computer and human conditions over all the trials. The bar extends one standard error above and below the mean.

Behavioural data shows that half the subjects in our experiment consistently attempted cooperation with their human counterpart.

Within this group, and within subjects comparison, they find that regions of prefrontal cortex are more active when subjects are playing a human than when they are playing a computer following a fixed (and known) probabilistic strategy.

Within the group of non-cooperators, we find no significant differences in prefrontal cortex between the computer and human conditions.

One possible explanation for our results is that within this class of games, subjects learn to adopt game form-dependent rules of thumb when playing the computer or when playing non-cooperatively with a human counterpart.

Cooperation requires an active convergence zone in prefrontal cortex, that binds joint attention to mutual gains with the inhibition of immediate reward gratification to allow cooperative decisions.

74

ApplicationsOXYTOCIN AND TRUSTING BEHAVIOR

Michael Kosfeld, Markus Heinrichs, Paul J. Zak, Urs Fischbacher & Ernst Fehr “Oxytocin increases trust in humans“ Nature 2005 In non-human mammals, the neuropeptide oxytocin has a key role in general

behavioural regulation, particularly in positive social interactions.

Oxytocin receptors are distributed in various brain regions associated with behaviour, including pair bonding, maternal care, sexual behaviour, and the ability to form normal social attachments.

Thus, oxytocin seems to permit animals to facilitate approach behaviour.

HP.: oxytocin might also promote prosocial approach behaviours (such as trust) in humans.

Recent neuroscientific finding: neuropeptides cross the blood-brain barrier after intranasal administration

75

76

Double-blind study design to compare: - trusting behaviour in a group of subjects who receive a dose of intranasal oxytocin - trusting behaviour in a control group of subjects who receive placebo. Experiment’s object trust game with real monetary stakes (29+29 subjects)

Hypothesis to test: oxytocin increases the trusting behaviour of investors the investors in the oxytocin group will show higher money transfers than those in the placebo group.

Two treatments

standard trust game risk trust game

In B the investor faced the same choices as in the trust game but in which a random mechanism, not the trustee's decision, determined the investor's risk.

The random mechanism in the risk experiment replicated the trustees' decisions in the trust experiment.

Therefore, the investors faced exactly the same risk as in the trust experiment

However, their transfer decisions were not embedded in a social interaction because there were no trustees in the risk experiment.

77

Experimental design

194 male students (mean age s.d., 22.0 3.4 yr) from different universities in Zurich 128 participants in the trust experiment and 66 subjects participated in the risk

experiment Exclusion criteria: medical or psychiatric illness, medication, smoking, drug or alcohol

abuse Subjects were instructed to abstain from food and drink (other than water) for 2 h

before the experiment, and from alcohol, smoking and caffeine for 24 h before the experiment

Participants were informed at the time of recruitment that the experiment would evaluate the effects of a hormone on decision making

16 individuals out of the original sample of 194 were excluded because of incorrect substance administration (7 in the trust experiment, 5 in the risk experiment) or their stated disbelief that the opponent in the trust game was actually a human being (4 participants)

Subjects received a single intranasal dose of 24 IU oxytocin (Syntocinon-Spray, Novartis; 3 puffs per nostril, each with 4 IU oxytocin) or placebo 50 min before the start of the experiment

Subjects were randomly assigned to the oxytocin or placebo group In order to avoid any subjective substance effects (for example, olfactory effects)

other than those caused by oxytocin, the placebo contained all inactive ingredients except for the neuropeptide.

78

Conclusion oxytocin increases the investors' transfer levels in the trust experiment but not in the riskexperiment oxytocin specifically affects trust in interpersonal interactions.

Explanationsa) oxytocin causes a general increase in prosocial inclinationsOxytocin should affect not only the prosocial behaviour of the investors but also that of

the trustees.But trustees given oxytocin do not show more trustworthy behaviour. At every positive transfer level (4, 8 or 12 MU), their back transfers are statistically indistinguishable from those of placebo trustees (Mann Whitney U-tests; P > 0.243, two-sided tests for each positive transfer level).

b) oxytocin does not increase the general inclination to behave prosocially. Rather, oxytocin specifically affects the trusting behaviour of investors.

c) effect of subjects' beliefs. Oxytocin might render subjects more optimistic about the likelihood of a good outcome. In order to address this question, we measured the investor's subjective expectation about the trustee's back transfer after every transfer decision. A Mann-Whitney U-test indicates that these expectations do not differ significantly between oxytocin and placebo groups at every feasible positive transfer level

d) oxytocin helps subjects to overcome their betrayal aversion in social interactions.

This explanation is consistent with the differing effects of oxytocin across the trust and the risk experiments, and is further supported by the fact that investors faced a considerable betrayal risk.

81

Many experimental economists seem to view their enterprise as akin to silicon chip production. Subjects are removed from all familiar contextual cues. Like the characters 'thing one' and 'thing two' in Dr. Suess' Cat in the Hat, buyers and sellers become 'persons A and B', and all other information that might make the situation familiar and provide a clue about how to behave is removed.

George Loewenstein (1999)

The context-free experiment is an elusive goal and not necessarily a good thing

Games in the laboratory are usually played without labels but subjects inevitably apply their own labels

A major discovery of cognitive psychology is how all forms of thinking and problem solving are context-dependent (language comprehension)

The laboratory is not a socially neutral context, but is itself an institution with its own formal or informal, explicit or tacit, rules

Internal validity - ability to draw confident causal conclusions from one's research

External validity - ability to generalise from the research context to the settings that the research is intended to approximate

Experiments have the reputation of being high in internal validity but low in external validity

Field studies of being low in internal validity but high in external validity

Innocenti–Lattarulo-Pazienza (2009)

Aim: to extend previous experimental evidence on travel mode choice by providing subject not only with information acquired through personal experience, but also with actual travel times of the alternative non chosen travel modes

Key Findings: subjects exhibit a marked preference for cars are inclined to confirm their first choices update imperfectly expectations on travel times

Experimental literature on travel mode choice relies widely on studies on route choice

Common object: coordination games, i.e. the payoff each traveler can achieve is conditional on her/his ability to diverge from or to converge with other travelers’ choices

Selten et al. (2007), Ziegelmeyer et al. (2008), Razzolini-Dutta (2009) provide laboratory evidence that choices between route A and route B generate Nash equilibria

Evidence from the field shows that these learning processes are affected by cognitive biases (Kareev et al. 1997, Verplanken–Aarts 1999)

To provide travelers with more accurate information on actual travel times does not necessarily increase their propensity to minimize travel costs (Avineri-Prashker 2006)

Information is better processed when travelers lack long-term experience on travel time distribution (Ben Elia–Erev-Shiftan 2008)

Cars are generally perceived as travel means giving people the sensation of freedom and independence

The costs associated to car use are undervalued because they not paid contextually with car use

Pollution or social costs due to car accidents are often neglected and not easily computable

These factors explain the presence of a general propensity to use private cars and of a psychological resistance to reduce it

Van Vugt et al. 1995, Tertoolen et al. 1998, Bamberg et al. 2003

62 undergraduate students (31 women and 31 men) from the University of Firenze

Computerized experiment

Between subject

Each session lasted approximately an hour

Average earnings 18.4 euro

a) Choice between Car or Metro - Metro travel costs are fixed, while car costs are uncertain and determined by casual events and traffic congestion

b) Choice between Car or Bus - Car and bus are both uncertain and determined by the combination of casual events and traffic congestion

Travelers’ utility only depends on travel times, which are converted in monetary payment

After each choice, subjects are provided of actual times of both available modes, but not of the probability distributions determining casual events

Metro Car treatment - the expected travel costs of car and metro were equivalent if the share of car users was not greater than 55%;

Bus Car treatment - the expected travel costs of car and bus were equivalent if the share of car users was not greater than 55%;

Bus 0.8 Car treatment, the expected cost of bus was 20% lower than car expected costs if the share of car users was not greater than 55%.

Table 8 Proportion of car choices by treatment (each five periods)

Period Metro Bus 1.0 Bus 0.8 1 0.70 0.60 0.59 5 0.67 0.67 0.35

10 0.60 0.47 0.35 15 0.57 0.67 0.47 20 0.57 0.53 0.53 25 0.77 0.53 0.41 30 0.67 0.73 0.71 35 0.70 0.60 0.71 40 0.60 0.53 0.53 45 0.67 0.60 0.53 50 0.73 0.53 0.53

Total 0.68 0.58 0.50

Table 11 Correlation coefficients between car choices and car costs

Treatment

N. of car choices at time t / Average car

costs of all the previous periods


costs of the previous ten periods


costs of the previous five periods

Metro vs. Car -0,049 -0,207 -0,200

Bus 1.0 vs. Car -0,195 -0,391 -0,251

Bus 0.8 vs. Car -0,200 -0,494 -0,440

One of the basic tenets of laboratory methodology is that the use of non-professional subjects and monetary incentives allows making subjects’ innate characteristics largely irrelevant

In our experiment, it is as if subjects take into the lab the preferences applied to real choices and stick to them with high probability

This inclination to prefer cars tends to override the incentives effect

Labels give subjects clues to become less and not more rational

In this case, subjects’ behavior depends more on prior learning outside the laboratory than on expected gains in the laboratory

Labels have the power to increase external validity with a minimal sacrifice of the internal validity

To test learning and cognitive models, it is necessary to remind and to evoke contexts which may activate emotions, association, similarities in the laboratory

The use of presentations with virtual reality (VR) visualisations can convey objectively this kind of information

A Virtual Experiment combines insights from virtual reality (VR) simulations in computer science, naturalistic decision making (NDM) and ecological rationality from psychology, and field and lab experiments from economics

The methodological objective of Virtual Experiments is to combine the strengths of the artificial controls of laboratory experiments with the naturalistic domain of field experiments or direct field studies

In a virtual experiment the internal validity of controlled lab experiments is joined with the external validity of field experiments

Visual information may reduce anomalies within non-market valuation studies

Losses are discounted at a lower rate than gains (Kahneman and Tversky 1974): people are indifferent to receiving £10 immediately and £21 in one year and indifferent between losing £10 immediately and £15 in one year

Consumers tend to over discount the gains to a greater extent than the losses that would result if the expected return turns out to be negative

Bateman et al. (forthcoming)

In the majority of choice experiments on gain-loss asymmetry the attributes of non-market goods are conveyed to respondents as a table of numeric and/or categorical data.

Compared to the standard presentation, preferences elicited in the Virtual Experiment are less variable and exhibit a significant reduction in asymmetry between willingness to pay for gains and willingness to accept for corresponding losses.

Fiore et al. 2009 Virtual Experiment to elicit subjective risk perception

from wild fires and the opportunity cost of public funds allocated to prescribed burns

Subjects experience four dynamic visual simulations of specific wild fires, with varying weather and fuel conditions. Simulations are selected to represent high and low risk of fire damage

Participants experience a sense of presence, a psychological state of “being there and take decisions closer to real behavior (with cognitive constraints )

Research ProjectLabsi

Centro Interuniversitario per l’Economia Sperimentale

to replicate the travel mode choice in a virtual experiment

http://trafficsimulation.org/

ALBO Research Projectfunded by Regione Toscana

to elicit factors of risk and job related stress in the workplace

http://www.progettoalbo.it/index.php?lang=en

by making interactive the simulation of “L’enterprise virtuelle” by Government of France

http://www.travailler-mieux.gouv.fr/

Pars destruens

Cognitive Biases Bubbles Individual decision-making Markets

Pars construens

Dual Process Theories Overconfidence Information processing Informational cascades

AvailabilityItems that are easier to recall are judged to be more common because they are noticed and reported more often (the ease with which regular web users can think of examples relating to the Internet revolution encouraged the market boom of the late 1990s)

RepresentativenessProbability assessment of a state of the world is based on the degree to which the evidence is perceived as similar to or typical of the state of the world (people tend ot rely too heavily on small samples and too little on large samples)

Anchoringpeople tend to be unduly influenced in their assessment of some quantity by arbitrary quantities mentioned in the statement of the problem (preference for the status quo or the default option)

Overconfidence(Psych) overoptimism about the individual’s ability

to succeed in his/her endeavors(Economics) to overassess the importance of

private information with respect to public information

Since the 1970s a lot of experimental and theoretical work has been devoted to describe attention orienting as a dual processing activity (Schneider and Shiffrin 1977, Cohen 1993, Birnboim 2003)

Selective attention is defined as "control of information processing so that a sensory input is perceived or remembered better in one situation than another according to the desires of the subject" (Schneider and Shriffin 1977, p. 4)

This selection process operates according two different patterns: controlled search and automatic detection

SELECTIVE ATTENTION

Controlled Search Automatic Detection

Controlled search is a serial process that uses short-term memory capacity, is flexible, modifiable and sequential

Automatic detection works in parallel, is independent of attention, difficult to modify and suppress once learned

System 1 collects all the properties of automaticity and heuristic processing as discussed by the literature on bounded rationality

System 1 is fast, automatic, effortless, largely unconscious, associative and difficult to control or modify

The perceptual system and the intuitive operations of System 1 generate non voluntary impressions of the attributes of objects and thought

System 2 encompasses the processes of analytic intelligence, which have traditionally been studied by information processing theorists

System 2 is slower, serial, effortful, deliberately controlled, relatively flexible and potentially rule-governed

In contrast with System 1, System 2 originates

judgments that are always explicit and intentional, whether or not they are overtly expressed

1. “Gaze Bias Parallels Decision Making in Binary Choices under Uncertainty”

with Alessandra Rufa, Francesco Fargnoli, Piero Piu, Elena Pretegiani, Jacopo Semmoloni (Eye-Tracking & Vision Applications EVA Lab)

2. “The Importance of Betting Early”with Tommaso Nannicini (Università Bocconi, IGIER, and IZA) e Roberto

Ricciuti (University of Verona and LabSi)

3. “Intra-Day Anomalies in the Relationship between U.S. Futures and European Stock Indexes”

with Pier Malpenga (Leo Fund Managers), Lorenzo Menconi (Corte dei Conti and University of Siena) e Alessandro Santoni (BefinLAb, Monte dei Paschi di Siena, University of Siena)

Both System 1 and System 2 are an evolutionary product. People heterogeneity as the result of individually specific patterns of interaction between the two systems

If eye movements and attention shifts are tightly tied, gaze direction could represent a signal of how automatic and immediate reactions (giving right or wrong information) to visual stimuli are modified or sustained by more conscious and rational processes of information collecting

Informational cascade - model to describe and explain herding and imitative behavior focusing on the rational motivation for herding (Banerjee 1992, Bikhchandani et al. 1992)

Key assumptions

Other individuals’ action but not information is publicly observable

private information is bounded in quality agents have the same quality of private

information

People have private information ("signals") and can also observe public information

Public information is a history of all the actions (not information) of predecessors

People are rational because they are assumed to update their prior probabilities by using Bayes’ rule to process the public and private information they possess

An individual herds on the public belief when his action is independent of his private signal

If all agents herd there is an informational cascade that may be both “wrong” or “right”

The theory of informational cascades assumes that decision makers behave rationally in processing all the available information

Experimental evidence points out how subjects exhibit in the laboratory various cognitive biases in deciding if entering or not a cascade:

One third of the subjects exhibit a tendency to rely on the mere counting of signals (Anderson-Holt 1997)

Subjects’ overconfidence consistently explains the deviations from Bayes’ rule (Huck-Oechssler 2000, Nöth-Weber 2003, Spiwoks et al. 2008)

Two events - Square and Circle - may occur with equal probability.

For each session, 9 students were arranged in a pre-specified order and asked to predict the state with a monetary reward for a correct prediction

Each subject observes: an independent and private signal (Private Draw)

which has a 2/3 chance of indicating the correct event

the predictions (Previous Choices) made by the subjects choosing previously

??

2/3

1/3

2/3

1/3

2/3

1/3

1/3

2/3

??

First screen (5 seconds)

2 sec

Private draw- PD (right)

Previous choice-PC (left)

5000 m sec

Private signal- PD (left)

Previous choice-PC (right)

1000 msec

1000 msec

500 msec

1000 msec

Private information(individual draw)

Public information(previous choices)

Latency of first fixation

N. of first fixations

% N. of first fixations

% Average duration of first fixation

NON-OVERCONFIDENT

0.306 sec 27 (13L+14R) 52.952.9 24 (13L+11R) 47.147.1 0.838 sec

OVERCONFIDENT 0.412 sec 13 (6L+7R) 81.281.2 3

(1L+2R) 18.818.80.523 sec

Others 0.191 sec 3 (2L+1R) 60.060.0 2 (0L+2R) 40.040.0 0.835 sec

Total 0.321 sec 43 (21L+22R) 46.846.8 25 (14L+15R) 53.253.2 0.775 sec

Initial allocation of attention (first fixation)

Results

19/04/23www.evalab.unisi.it 133

0 20 40 60 80 100 1200.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

time up to decision

Likeli

hood

Group "overconfident"

p vs. t

fit 1

OC

NOC

Gaze Clustering. •Cluster I= Early DM (heuristic)•Cluster II= Late DM (DM modulators elaboration , reinforcement)•Overconfidents could make decision erlier and then reinforce it

Overconfident subjects allocate the first fixation (initial attention) toward private draw and take more time than others to decide if the private signal is on the right or the left of the screen.

Non overconfident subjects allocate their initial attention to both kinds of information without exhibiting any particular bias

In terms of the Dual Process theory, our findings support the hypothesis that automatic detection, as inferred from gaze direction, depends on cognitive biases.

The heuristic and automatic functioning of System 1 orients attention so as to confirm rather than to eventually correct these biases.

The controlled search attributable to System 2 does not significantly differ across subject types.

Dataset 1.205.000 bets on the Italian Soccer League Serie A (January 2004- November 2004)

Mainly small bettors on multiple bets (on

average 5 euros)

Average odd of each event 2.49

Young men (18-30 years old) from Southern Italy

Table 4 – Baseline regression: timing_late

(1) (2) (3) (4) (5) (6) Timing_late 0.013*** 0.013*** 0.010*** 0.013*** 0.013*** 0.011*** [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] Home wins 0.184*** 0.184*** 0.183*** 0.184*** 0.184*** 0.183*** [0.002] [0.002] [0.002] [0.001] [0.001] [0.001] Strong wins 0.290*** 0.290*** 0.305*** 0.290*** 0.290*** 0.305*** [0.002] [0.002] [0.002] [0.001] [0.001] [0.001] Gameweek -0.003*** -0.004*** -0.003*** -0.004*** [0.000] [0.000] [0.000] [0.000] Other events 0.024*** 0.024*** 0.023*** 0.024*** 0.024*** 0.023*** [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] Amount user 0.017*** 0.018*** 0.011*** 0.018*** 0.018*** 0.011*** [0.006] [0.006] [0.004] [0.002] [0.002] [0.002] Main teams 0.070*** 0.070*** 0.068*** 0.070*** 0.070*** 0.068*** [0.002] [0.002] [0.002] [0.001] [0.001] [0.001] Dummy gameweek NO NO YES NO NO YES Individual FE NO NO NO YES YES YES Gameweeksq NO YES NO NO YES NO Observations 1,205,597 1,205,597 1,205,597 1,205,597 1,205,597 1,205,597 N. of individuals 7,093 7,093 7,093 7,093 7,093 7,093

Columns (2) and (5) include the variable gameweeksq, which is significantly positive only in (5), but extremely small (see text).

We do not detect any learning during the course of the season

Statistically significant difference of performance between early bettors (betting before the last day) and late bettors (betting the day of the event)

We propose to explain the lower performance of late bettors as due to noisy and redundant information that is unknown to early bettors.

Early bettors can adopt more than late bettors simple heuristics, based on the actual relations between a simple criterion value (i.e., home team winning) and some cues (i.e., team ranking or last match result) and on the interrelations between these predicting cues.

Our findings support the hypothesis that simple heuristics – fast and frugal à la Gigerenzer - perform better than complex information processing steps in environment affected by noisy and redundant information.

The relationship between the price series of stocks and futures is one of the most widely researched topics in finance

Empirical evidence that the realignment of prices in the two markets is not instantaneous

Stock indexes follows the corresponding future indexes with a time lag ranging from five minutes (Stool-Whaley 1990) to forty-five minutes (Kawaller et al. 1987).

We provide evidence on the relationship between the price dynamics of the U.S. S&P 500 index futures and the three major European stock indexes (CAC 40, DAX, and FTSE 100)

Our findings show that the widely documented strong correlation between futures and stock indexes extends to this specific cross-country case.

The correlation is particularly strong in the opening and closing of the European

Figure 4.1.1 Correlation between S&P futures and DAX, CAC, FTSE stock indexes from January to May 2010 (30 minutes)

Table 4.1.1 Correlation between S&P futures and DAX, CAC, FTSE stock indexes from January to May 2010 (30 minutes)

Time Period (CET time)

DAX CAC FTSE

09:00-09:30 76.68% 83.66% 70.49%

09:30-10:00 77.67% 85.42% 75.62%

10:00-10:30 73.91% 76.99% 69.76%

10:30-11:00 74.01% 75.94% 67.38%

11:00-11:30 70.69% 77.99% 73.02%

11:30-12:00 67.34% 73.95% 66.38%

12:00-12:30 72.19% 75.39% 71.27%

12:30-13:00 69.17% 72.56% 70.17%

13:00-13:30 61.88% 63.79% 57.11%

13:30-14:00 78% 79.42% 70.52%

14:00-14:30 72.43% 75.98% 67.67%

14:30-15:00 77.69% 81.82% 72.08%

15:00-15:30 44.41% 52.54% 45.23%

15:30-16:00 76.75% 81.07% 84.59%

16:00-16:30 85.25% 90.36% 86.9%

16:30-17:00 77.54% 84.2% 82.06%

The correlation drops quickly and remarkably between 13:00 and 13:30 (CET time)

This fall is interpreted as derived from the release of news coming from U.S. corporate announcements scheduled each day at 7:00-7:30 (US Eastern time)

US and European markets react differently to the release of new information. In US future markets traded volumes decrease until the announcements are made. In European markets, information asymmetry influences price sensitivity by originating arbitrage opportunities, due to the imperfect international integration of financial markets

The correlation fall originates time-zone arbitrage opportunities between US futures and European stock markets

Traders do not exploit this opportunity because the European markets react more slowly to the release of new information than US markets

Asyncrony of information processing due to information overload which is confirmed by the the decrease of traded volumes

“Highly accessible impressions produced by System 1 control judgments and preferences, unless modified or overridden by the deliberate operations of System 2.” (Kahneman and Frederick 2002)

System 1 orienting choice

System 2 reinforcing choice

Heuristic processes of System 1 select the aspect of the task on which attention is immediately focused

Analytic processes of System 2 derive inferences from the heuristically-formed representation through subsequent reasoning

This dual account of attention orienting may explain the emergence of cognitive biases on financial markets whenever relevant information is neglected at the heuristic stage.

Ph.D. in Economics 2011-2012 University of Siena Course Decision Theory INDIVIDUAL CHOICE BEHAVIOR...

Documents

Transcript of Ph.D. in Economics 2011-2012 University of Siena Course Decision Theory INDIVIDUAL CHOICE BEHAVIOR...