Experimental economics

Mylene Lagarde, LSHTMJohannesburg, Nov 2007

HEPNet Workshop

Overview

1. Background and characteristics of experimental economics

2. Applications• Classic use: testing theories• Recent developments: social preferences

3. Designing an experiment• An example• Main features of an experiment• Some classic games

4. Relevance for health systems research

5. Possibilities and limitations of experimental economics

1. Background and characteristics of experimental economics

Origins : the willingness to test economic assumptions

• Micro-economics relies heavily on a number of assumptions

• Preferences/mechanisms are hard to observe in natural environments

• Need to test and therefore potentially refute these assumptions in a scientific way? – Market classroom experiment : Chamberlain (1948) and his student V. Smith (1962)

The influence of game theory• Game theory attempts to model strategic

interactions– How do agents choose strategies which will maximize

their return, given the strategies the other agents choose

• They use simplified structures for modeling strategic behavior– Games provide a formal modelling approach to social

situations in which decision makers interact with other agents

• Application to many problems– Political science, economics, etc.

Other major influences

• Psychology– Psychologists have used experiments with participants to

test some assumptions on fundamental behaviours: authority

• Behavioural economics– Informing economic theory with lessons from psychology

– Challenges neo-classic assumptions of economics (rationality, self-interest, stability of preferences, risk aversion, etc.)

Principles of experimental economics• To create an (economic) situation in a neutral

environment (lab) which is:– real

• Real people…• … participating for real monetary stakes• …following real rules

– simple – controlled

• Motivations• Initial information• Interaction processes

– reproducible

• And observe behaviours and outcomes

A method of empirical investigation

1. Testing theories and establishing empirical regularities as a basis for new theories

2. Elicitation of preferences: attitude towards risk, fairness, altruism, trust, time preferences

3. Testing policies: wind tunnel experiments

A young and blossoming field

The 2002 Nobel Prize in Economic Sciences

"for having established laboratory experiments as a tool in empirical economic analysis, especially in the study of alternative market

mechanisms"

"for having integrated insights from psychological research

into economic science, especially concerning human

judgment and decision-making under uncertainty"

Vernon L. SmithDaniel Kahneman

2. Some applications

•Classic use: testing theories•Recent development:

• Field experiments

• Revealing social preferences

Main areas of application• Financial economics

– Information diffusion and aggregation, price setting mechanisms, irrationality, bubble formation

• Industrial economics– Design of incentives and contracts (improving performance), auction

designs (electricity markets, air slot allocation, etc.)

• Environmental economics– Regulations to use common resources (fishery), to design pollution

permit markets, etc. (public goods, externalities)

• Agricultural economics– Real market experiments: food auction, Actual WTP for cereals, etc.

Main fields of research• Individual choices

– inter-temporal choices, risk aversion, social preferences, etc.

• Strategic Interactions (game theoretic hypotheses)– contracts, conflicts/coordination, public goods, etc.

• Industrial organization– Market efficiency– Market power issues (development of collusion,

cooperation)– Market design

Testing theories

• Neoclassical theory works (relatively) well for markets where important assumptions hold (prop rights well defined, perfect information, low transactions costs)

• BUT not always….

• EE are simple tools which allow to isolate/measure the reasons for a model’s failure

• Models and principles that survive the testing can be used to address field questions

Testing regulations/policies

• Financial markets– Testing how to regulate markets to prevent irrational

behaviour, the formation of bubbles, etc.

• Auction design– Testing one predictions of models with real individuals

in a controlled environment

• Environment economics– How to regulate the use of rare resources– Regulations and externalities (pollution permits, etc.)

The spectrum of experiments

• Historically, EE has been applied in lab experiments– Participants = graduate students

• Computerized game or paper-based• Neutral frame

– To test theories, policies

• Move lab games into the field: a new practice – Paper based– Participants are not students, but ‘real’ people– Experiments are tailored to a field context/policy, and less

neutral– Experiments are used as tools to measure some values

The importance of social preferences

• “Social preferences” – “preferences”= choices made by individuals , tradeoffs btw different

collections of things they value (time, money, prestige, leisure, etc.)– “social preferences”= how people rank different allocations of material

benefits to themselves and others

• Existence and importance of social preferences– Social preferences have an impact on the enforcement of social norms:

abundant literature on the effects of fairness, inequality (absence of), trust on economic behaviour, etc.

– Evidence of adverse effects of (monetary) incentives if social preferences not accounted for (voluntary work, intrinsic motivation)

Revealing social preferences• Difficult to identify them, even more to measure them

– How do you observe altruism ? Fairness ? Inequality aversion (relative to each other)? Risk aversion ?

• Why use experiments to measure them?– Surveys on trust, altruism may be biased – Experiments are likely to suffer less from response bias to reveal fundamental

preferences because of monetary stakes– Experiments allow quantification

• What types of preferences can experiments measure?– Social preferences: norms of altruism, fairness, trust, trustworthiness, aversion

for inequity.– Other preferences: risk aversion, time preferences.

Social preferences in 15 small scale societies (1)

• Henrich et al. (AER 2005, Science 2006)

• Setting: project led by anthropologists, in 15 remote societies on 4 continents

• Objectives: to investigate how social preferences vary across cultural environments

• Methods– Measures of altruism, fairness and aversion for inequality – Measures of market integration and other aspects of socio-economic

life in these societies• Results

– preferences are not exogenous (as assumed by neo-classic economics) but shaped by the economic and social interactions of everyday life

– Substantial variation among populations of aversion for inequality which co-evolves with norms of fairness/altruism

– the canonical model of the self-interested material payoff-maximizing actor is systematically violated

Social preferences in 15 small scale societies (2)

Using EE to measure preferences (1)

• Karlan (AER 2005) • Setting: Peru, clients of a micro-credit program• Objectives: investigating the determinants of default payment

and saving • Methods

– uses survey and experimental measures of social capital -trustworthiness and willingness to cooperate;

– Observes borrowing behaviour over 1.5 year

• Findings– Significant negative correlation between (magnitude of) trustworthiness

and (1) probability of default , (2) dropout of dropping out of the program and (3) volume of savings

– Some individuals are just not trustworthy and will not repay their loans?– TG can be a valid measurement tool for trustworthiness, less obvious for

‘trust’ which is too context specific

Using EE to measure preferences (2)

• Carpenter and Seki (2006) and Carpenter and Seki (2004) • Setting: Japan, individuals involved in different degrees in

fishing activities and are exposed to different degrees of competition

• Objectives: – to investigate the level of competition in a work environment can

explain the propensity to cooperate– to investigate whether the individual propensity to cooperate affects

productivity• Methods

– uses experimental measures of cooperation – Uses surveys to measure productivity and level of competition

• Findings– The higher the degree of competition the less cooperative

individuals are– The more cooperative individuals are, the higher their productivity

A new but growing field

• Many other examples of games used to measure social preferences– To see whether they help explain actual behaviours– To use them as outcomes (e.g. impact of education program

on altruism amongst children)

• Currently implemented in Mexico: games piggy-backing on a national survey – “to provide new insights into the role of preference

heterogeneity in explaining economic decisions and enable new tests of hypotheses that seek to explain family behaviour”

3. Designing an experiment

• Let’s play a game !

• Main characteristics of the game

•Examples of other games

Basic rules

• Please try to follow all the rules:– Listen and read carefully the instructions

– If you have questions, raise your hand and I will come and answer it privately

– Do not talk with each other, even when the experimenters are calculating the payoffs between rounds

• 100 ECU = US$ 1

Example with 3 players• Players 1, 2 and 3 are given 200 ECU each• Their decisions:Player 1 invests 0 in A

Player 2 invests 100 in A

Player 3 invests 200 in A

• Return on investment from A = 300 x 1.5=450• Return for all three players= 450/3= 150• Endowments at the end of round 1:Player 1 has 200 +150 = 350

Player 2 has 200 -100 +150 = 250

Player 1 has 200 -200 +150 = 150

Total invested in A = 300

Steps

1. Write your ID number on your response sheet

2. Write the amount you want to invest in A

3. Detach the bottom section of your answer sheet, fold it and place it in the box

4. Wait until you know the value of individual payoffs

5. Calculate yourself the value of your endowment at the end of the round

6. Play the next round

Public good game: interpretation and results

• Interpretation:– Propensity to cooperate (vs. free-ride) in a group, reciprocal

behaviours in groups– Use of different types of regulations (external, communication) in

different contexts: team compensation, cooperative production/maintenance, use of common resources

• Results:– Prediction: each player will contribute nothing (individual welfare

vs. collective welfare with public goods bringing externalities)– One-shot game: 50% contribution ; contributions diminish over

time (final period: contribution=0)– What contributes to increase cooperation

• Communication• Possibility of individual punishment• Disclosure of free-riding

What would be different “for real”

• Smaller group

• Participants don’t make their own calculations !

• You would be playing for real money

• Several “treatments” could be tested

Game procedures (1)• Abstract setting

– Anonymous players, playing once, for money, without communication

– Not lifelike, but baseline to observe effects of any variant (communication, non-anonymity, etc.)

• Participants: – college students recruited with minimal knowledge of the task (e.g.

Study on decision making)

– More “real” people that you may want to observe

• Organization:– Ensure anonymity: private box, random drawing

– Ensure credibility: existence of recipients if not present, real incentives paid at the end; DON’T LIE

Game procedures (2)• Instructions to describe rules:

– Plain abstract language (benchmark)– Use letters/neutral framing– Avoid some words “sharing”, “helping”, “trust”– Examples, quiz

• Design characteristics– Multiple rounds vs. One-shot games

• Depends on the game• If “equilibrium” situation, then multiple rounds to allow learning (then

rematching)

– Treatments vs. individual measurements

Game procedures (3)

• Giving interactions to participants in multi-player games:– Direct feedback– “Strategy method”: players make choices conditional on

every single response of other player

• Treatments– Several groups: 1 difference per group (rules, framing, etc.)– Allows to measure the effect – Not necessary if objective= measurement of preferences for

all individuals

Components of an experiment

• Institution (rules of the game)– Feasible actions– Sequence of actions– Information given – Knowledge of participants

• Framing of instructions– Abstract framing : basic incentives only– Framing matching reality to get at social norms:

• Participation to maintenance of a water well• Health worker, community, patient

– Interesting to compare abstract vs. real framing

Experimental variables to define

• Procedural design– Instructions– Illustrative examples and tests of understanding– Criteria for answering subjects’ questions– Trial periods

• Experiment characteristics– Payment– Recruiting subject pool, number of subjects– Matching procedures when interaction

• Environment– Date and place– Computerized or paper-based– Irregularities which occurred

Analysis of experiments

• Most analyses do not require sophisticated methods

• Measures of social preferences– Creation of proxies based on individual choices

• Descriptive analysis at group level underlying– Outcome variables under each treatment– Influence of simple socio-economic variables

A few examples of other games

Dictator Game

PLAYER 1 PLAYER 2

X $$

% of X

= measure of altruism

DG - interpretation and results

• Interpretation– Measure of altruism; aversion for inequality (knowledge that

the other is poor), etc.– Relates to charitable giving

• Results– Prediction: no sharing BUT on average individuals give 20%– Allocations increase with needy/deserving recipients and

decrease with anonymity– Norms vary across settings/countries– Game sensitive to setting, etc.

Ultimatum Game

PLAYER 1 PLAYER 2

X $$

% of X

= measure of preference for equity/fairness

AGREES:

Deal is made

REFUSES:

Both get NOTHING

UG – interpretation and results• Interpretation

– Measures of social norms of sanction– Relates to pricing in a monopoly situation, or last minute settlement

• Results:– Prediction: proposer sends the smallest possible unit (always

accepted by recipient because better than nothing)– On average proposers offer 30-50%– Offers below 20% are rejected half of the time– Norms vary across settings and are well accepted (offers will be

readily made according to norms)– Effects of competition:

• Btw proposers increases offers• Btw recipients diminishes threshold of acceptance

– No effect of anonymity

Third Party Punishment Game

PLAYER 1 PLAYER 2

X $$

% of X

= altruism under social norms pressure

= measure of preference for equity/fairness

X $

PLAYER 3

WATCHES

SANCTION

- k $

- Y $

TPP – interpretation and results

• Interpretation– Behaviour of punisher: Reveals aversion for

inequality (against a shared norm): people who dislike it will take costly actions to reduce inequality

• Results– Prediction: No allocation from dictator ; observer

never punishes dictator– The less dictator allocates, the higher is the sanction

Trust game

PLAYER 1 PLAYER 2

X $$

% of X 2 x (% of X)

Part of

2 x (% of X)

= measure of trust

= measure of trustworthiness

Trust – interpretation and results

• Interpretation– Trust of investor and reciprocity of trustees

(trustworthiness)

– Exchange of services without possibility to bind the second movers

• Results– Prediction: (expected) repayment from trustee: 0 and

Entrusted/invested amount: 0

– On average investors give 50%, while trustees repay slightly less than that

– The bigger the investment, the bigger the repayment

Bribery game

Private citizens

Public servants

Other members of society

$B

$$

$$

$$

- Y $Expected cost of being punished/ caught

$$$

- $$Expected cost of being punished/ caught + cost of producing the service

- $$

Results from bribery games

• Very few examples, different versions/level of complexity

• Barr and Serra: – Experiments on students coming from different

countries– positive correlation between internalized norms

(Transparency international index) and corruption in the game

– Contradicts 1 other experiment

4. Possible applications to health system issues

• Investigating corruption • Revealing the influence of social preferences• Health insurance• Designing incentives, contracts, etc.

Trust and trustworthiness

• Studies have emphasized the importance of trust– In the workplace

– For patients towards health workers

• Experimental games could:– Provide a way to measure trust and trustworthiness in

different framed contexts

– See how trusting behaviour differ when played with anonymous players/ nurses with doctors / doctors with themselves, etc.

Experiments as measurement tools

• Quantification of social preferences– altruism, aversion for inequity, trust, time preference,

etc.

• Use the variables to test their association with:– health seeking behaviour (time preferences)– Perceived quality of care (trust)– Providers’ behaviours (different cooperative

behaviours)

• Objective:– Descriptive– Prescriptive: link with other theories ; test new policies,

etc.

Health insurance

• When people are free to choose whether and how they secure their wellbeing, do they make predictable and rational decisions that are consistent with the objective of reducing vulnerability to health risks?

• Are there differences across individuals that can explain decisions to enroll/not enroll?– Impact of time preferences on decision to enroll in a CBI ? – Impact of risk aversion on propensity to enroll

Investigating corruption• Barr et al. (2004): the public servant’s dilemma• Setting: Ethiopia, nursing students • Objectives:

– to investigate the determinants of corrupt behaviour• Methods

– uses a designed experiment with 3 types of players (monitor, health workers and community members)

• Findings• Embezzlement of resources is affected by

– Earnings HWs (small effect)– Observability of embezzlement behaviour and likelihood to be

punished– Legitimate monitoring (Election of a member of the community vs.

random designation)– Framing increases variance in behaviours suggesting different

professional norms

Plenty of other possible games !• Games designed to reproduce an existing

environment – More complex, specifically designed/tailored– Modelling choices faced by actors in a particular situation– Reproduce incentives and main characteristics of these

choices– See which regulations may work better

• Objectives– To better understand the determinants of behaviours

5. Possibilities and limitations of experimental economics

• What experiments can / can’t do

• Advantages

• Limitations

Experiments are one of many research tools

• Qualitative methods• Surveys: Econometric/statistical analysis of

existing data• Experimental methods• Real-world pilots/trials

• Each has its relative strengths/weaknesses– Complements, not substitutes

When are experiments useful?

• To reveal or measure social preferences (altruism, trust, etc.)

• To understand behaviours/phenomena that can hardly be observed in the reality– Measure (relative) values

• If the data don’t exist, then create the data you need– If it’s never been done, how do you know what works?– Test new policies/ incentives / types of regulatory

mechanisms– Preliminary step, before actual pilot study in the field

Advantages of Exp Econ (1): enhanced control

• It is known which variables are exogenous and which are endogenous

• Many variables that cannot be directly observed in the field can be observed in the lab. – Quantification of reaction to incentives, cut-offs (risk

aversion)

• Subjects are randomly assigned to the treatment conditions – rules out selection bias.

Advantages of Exp Econ (2):avoiding some biases

• Motivation (payment)– avoid potential biases of responses obtained through classic

survey instruments which can reflect a “purchase of moral satisfaction”

• Language: – neutral phrasing, avoid framing effects that influence

answers

• “Double blind”– Some designs allow complete anonymity and avoids

experimenter effects and other-regarding concerns

Example: incentive program (P4P)

• Experiments could help understand:

– Relative efficiency of different types of rewards/sanctions on an experimental outcome

– Design of incentive program:

• individual or group-based and their impact on free-riding/gaming

• Impact of possibility to observe efforts or not

• Experiments could not answer:

– Magnitude of effect on performance/quality of work, etc.

– Which value of incentive for a particular task (WTP, DCE)

Example: health insurance

• Experiments could help understand:

– Time preferences of different groups of population

– Risk aversion of different types of populations regarding low and high probability events

• Experiments could not answer:

– Which service package would

– Which value of premiums could be acceptable (WTP, DCE with service package as well)

– Which type of management (community based, facility-based, etc.)

Limitations of Exp Econ• Internal validity: do the data permit causal

inferences?– a research study has internal validity if the outcome is a function of the

variables that are measured/ controlled/ manipulated in the study – Therefore internal validity of experiments is a question of proper

experimental controls and correct data analysis.

• The method is not realistic and lack external validity – A research study has external validity if the results obtained would apply

to other similar programs or approaches. – Problem of realism of “abstract” setting / simplistic modelling– Problem of representativity/realism: are experimental subjects

representative for out of sample applications?

Responses to lack of realism• Most economic models are unrealistic in the sense that they

leave out many aspects of reality to simplify it...

• Simplicity as a virtue?– because it enhances our understanding of the interaction of relevant

variables. – Because it allows to get at underlying values/ reflexes

• Whether realism is important depends on the purpose of the experiment. – If testing a theory or understanding the failure of a theory, then the

evidence is important for theory building but not for a direct understanding of reality.

– If EE is used to better understand real behaviours, then efforts must be made to frame the experiments and make them as close to real as possible

Ethical issues

• Transparency of motives– Even if not being deceptive, usually not “honest” about motives – When deception is involved, potentially more serious.

• Inducing decisions– The problem of the size of stakes / bribing

• Emotional distress– subjects may learn something about themselves not like

(selfishness, unacknowledged racist preferences)– Even more problematic when not anonymous (to study effects of

social norms)