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Parier sur l’économie expérimentale pour résoudre les problèmes actuels. Claude Montmarquette Les journées de l’économie Lyon, 20 novembre 2008. Qu’est-ce que l’économie expérimentale ?

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parier sur l conomie exp rimentale pour r soudre les probl mes actuels

Parier sur l’économie expérimentale pour résoudre les problèmes actuels

Claude Montmarquette

Les journées de l’économie

Lyon, 20 novembre 2008

slide2
Qu’est-ce que l’économie expérimentale ?

Méthodologie crédible de recherche qui permet de recréer et d’étudier dans un environnement contrôlé en laboratoire :

·L’importance de chaque motivation particulière (recherche du gain, besoin de réciprocité, réaction aux changements institutionnels,…) dans la prise de décision des agents.

·Sous conditions de risque, d’incertitude ou d’équivalence certaine, permet de tester les hypothèses exactes postulées dans les modèles et d’isoler l’influence de certaines variables. On peut analyser et comprendre l’éventuelle différence qui existe entre les prédictions théoriques à l’équilibre et les résultats tant expérimentaux qu’observés dans la vie quotidienne.

slide3
Qu’est-ce que l’économie expérimentale ? (suite)

· Rend possible la comparaison entre les environnements, les institutions et les politiques incitatives afin d'en évaluer l’efficacité relative. Cette approche est une plate-forme flexible permettant d’évaluer de nouvelles politiques et de nouveaux « designs » institutionnels sans avoir à subir les coûts sociaux et privés associés à leur mise en place.

·Permet de tester les implications de certaines politiques sociales ou de décisions de gestion sans avoir à réaliser des projets coûteux qui sont plus souvent qu’autrement mis en place avec des paramètres considérés ex post comme ayant été mal choisis ou spécifiés.

·L’économie expérimentale aide à la collecte de données empiriques pertinentes et fiables.

des distinctions
Des distinctions….
  • Expériences sur le terrain (field experiments): participation de différentes populations et permet de refléter les choix des individus dans leur milieu et contraintes naturelles
  • Expériences naturelles: formidables si possibles; situation peu fréquente et permet peu de traitements
  • Trend actuel est de combiner le labo et le terrain
slide5
Est-ce que les résultats obtenus sont transférables dans la réalité ?

Plusieurs réponses :

1.En économie expérimentale, les participants sont payés selon leurs décisions, comme dans la vraie vie. Si c’est le cas, pourquoi existerait-il des différences ?

2. Plusieurs études allant de la réalité vers le laboratoire ou du laboratoire vers la réalité ont prouvé le caractère transférable des résultats.

aide la solutions de probl mes actuels
Aide à la solutions de problèmes actuels

Notons d’entrer de jeu qu’il est impensable de recommander des politiques ou des solutions relativement aux problèmes étudiés sans comprendre les comportements des individus et leurs préférences. l’EE a consacré et continue à le faire beaucoup d’efforts à l’étude des comportements individuels, notamment relativement à leur attitude vis-à-vis le risque et vis-à-vis leur impatience à consommer.

de quels probl mes peut il s agir
De quels problèmes peut-il s’agir?
  • En principe, la limite des problèmes examinés est lié à l’imagination du chercheur à développer un protocole pertinent. Le défi à cet égard est de réussir à simplifier une situation complexe tout en maintenant la pertinence de l’analyse. L’expertise des analystes et les moyens technologiques disponibles repoussent continuellement les frontières. Historiquement, l’analyse expérimentale est passer de la validation de la théorie des jeux à des applications de politiques liées à la firme, au marché et à l’état.
exemples de probl mes
Exemples de problèmes
  • Ressources Naturelles et politique environnementale:
    • Mise aux enchères des droits d’émission
    • Marchés concurrentiels d’énergie électrique
  • Politique industrielle et réglementaire:
    • Affection des ressources en espace
    • Divulgation d’information
    • Règles fiscales et procédures de vérification
exemples de probl mes1
Exemples de problèmes
  • Investissement en éducation et en santé
  • Politiques de financement de l’état
  • Fraudes fiscales
  • Marché du travail et participation
  • Politiques industrielles
a study sponsored by human resources development canada
Will the Working Poor Invest in Human Capital? A Laboratory Experimentby Eckel, Johnson and Montmarquette SRDC Working Paper 02-01, February 2002

A study sponsored by

Human Resources Development Canada

slide11
Key Research Question

Given the right incentive, will the working poor save to invest in human capital?

slide12
Objectives of the experiment
  • Laboratory experiment can be used as a complementary approach to generate valuable information for the design of social experiments
  • SRDC wanted to shed light on the behaviour and preferences of the workingpoorwith respect to saving for learningactivitiesbeforelaunching the learn$ave demonstrationproject
three research questions
Three research questions
  • Will the working poor invest in various assets?
  • Are these subjects willing to delay consumption for substantial returns?
  • How do these subjects view risky choices?
slide14
Experimental Instruments

Two instruments:

  • Information questions (43)
    • Socioeconomic
    • Behavioural
    • Attitudinal
  • Compensatedquestions (64)
slide15
Compensated Questions - 64
  • Investment Preferences
      • Cash v. Investment choices
  • Time Preferences
      • Cash v. Cash later
  • Risk Preferences
      • Cash v. Risky cash
slide16
Sample Compensation Question From the Experiment

You must choose A or B:

􀂾 Choice A: $100 one week from today

􀂾 Choice B: $400 in your own training or education

slide19
Labour Force Participants

% of participants choosing family member’s education over $100 one week from today

slide21
What Have We Learned ?
  • In general, the working poor are risk averse and impatient
  • Nevertheless, many can be induced to invest in their own education
  • 44 percent accepted offer analogous to learn$ave (3 to 1 match)
  • Overall, own educational expenses was preferred to family member’s education and retirement savings
    • not true for non-labour force participants
  • Some (16%) couldn’t be induced to invest in any asset even when return approached 500%
slide22
What Have We Learned ?
  • The more patient people are, the more likely they are to invest in their own education
  • The more risk-averse subjects are, the less likely they are to invest in their own education.
  • Savings programs may benefit from higher take-up rates if they
    • Offer high returns
    • Stress absolute returns
    • Allow short term savings horizons
slide23
Fostering Adult Education: A Laboratory Experiment on the efficient use of loans, grants and savings incentivesby Jonshon, Montmarquette and EckelSRDC Working Paper 03-09, December 2003

A study sponsored by

Canada Student Loans Directorate and Applied Research Branch

Human Resources Development Canada

object of the experiment
Object of the experiment

To address a particular set of specific policy issues:

  • How do various types of learning subsidies (grants and loans) affect the participation rates in adult education?
  • Would the availability of incentives for part-time studies discourage full-time studies?
  • What is the extent of windfall gain resulting from different levels and types of financial incentives?
  • What are the “barriers” to participation in adult education?
      • Lack of information
      • Lack of time
      • Loan aversion
      • Fear of Failure
      • Preference for the present
      • Lack of readiness to learn
the experiment
The Experiment

Focus of the full study is on four sets of measures:

1. Experimental preference measures

  • consumption over time
  • risky choice alternatives

2. Survey measures: demographics and attitudes

3. Numeracy Assessment

4. Willingness to invest in post-secondary education

  • Grants
  • Loans (regular and income-sensitive repayment – ISR)
  • Matched-savings grants
survey measures
Survey measures
  • Demographics
    • Age, gender, income
  • Labor market and educational status
  • Attitudinal measures
    • Planning, debt
  • Barriers to education
    • Skills, dispositional, situational
example of risk aversion decision
Example of risk aversion decision

Choice A

  • $120.00 for sure

Choice B

  • 80% chance for $175 and

20% chance for $0

example of time preference decision
Choice A

$65 today

Choice B

$130 one year from today

Example of Time Preference Decision
cash vs investment choice
Cash vs. Investment Choice
  • Cash alternative made the choice of investment costly to the subject
  • Results used to calculate elasticities of demand for education with different types of subsidy
  • Through their choices, subject reveal their preferences for education when financed by:
    • Grants
    • Loans
    • ISR loans
    • Matched savings
determinants of choosing 1000 grant over cash ordered probit 801 observations
Labour Force attachment

Immigrants, disabled

Willingness to save (decision)

Positive attitude with respect to Education and Labor Market

Mathematical Competency

PSE experience

Age

Employee with education supplement

married

Children (older)

HS equivalency

Determinants of choosing $1000 Grant Over Cash (Ordered Probit, 801 observations)
labor market information session
Labor Market Information Session
  • How does information influence
    • Knowledge?
    • Attitudes?
    • Investment?
labour market information treatment
Labour Market Information Treatment

Initial

experiment

More

research?

No further action

No

Yes

Good general understanding of labourmarket or received educational compensation

No further action

Screen

Relatively poor understanding

of labour market

Random assignment

Comparison:No action

Treatment:LMI session

Follow-upexperiment

what we hope to learn
What we hope to learn
  • Overall, Is there evidence of Debt Aversion?
  • Are certain types of students prone to Debt Aversion?
determinants of choosing more education after the lmi session
Determinants of choosing more education after the LMI session

Probability of choosing more education for the young participants goes up by 15 percentage points or by 33%!

  • From 42% to 57%
what have we learned
What have we learned?
  • Experimentally measured individual characteristics, such as time preference and risk preferences, can explain variability in the decision making process as much as demographic and social characteristics.
  • Overall, participants were sensitive to different levels of incentives and different forms of financing
  • LMI interventions can make a difference
slide40

Willingness to Borrow: Using lab experiments to examine debt aversion among Canadian high school students

The Canada Millennium Scholarship Foundation

2008

research questions
Research Questions
  • Does the willingness to borrow vary significantly among types of students?
  • It is believed that students or potential students belonging to low SES families, Aboriginal families or first generation students’ families are less likely to be willing to borrow (doubt benefits of PSE, low likelihood of success).
  • How big a problem is debt aversion among these populations?
  • Are there other socio-economic groups that are more likely to be less willing to borrow?
proposed sample
Proposed Sample
  • 1400 12th graders and CEGEP students
  • Manitoba, Ontario and Quebec and Saskatchewan
  • Aboriginals
  • Rural/Urban
  • Low and High SES
data collection
Data Collection
  • Student Survey (web)
  • Parental Survey (Web or Tel)
  • Numeracy Assessment
  • Experimental Measures
protocol
Protocol
  • Info packets delivered to selected schools
  • Parental Consent Parental Survey
  • Students (pre-session) web survey
  • In-school Session ($20)
    • Practice Decisions
    • Experimental Decisions
    • Numeracy Assessment
    • Payoff
student survey
Student Survey
  • Educational ambitions
  • Expectations with regards to ambitions
  • Perceived obstacles to pursuing PSE
  • Financial means at student’s disposal
  • Debt aversion
  • Experience with debt
  • Educational background and experiences
  • Parent’s education and economic status
  • Inter-temporal orientation (planning ability)
  • Attitudes towards risk
  • Aspiration level
  • Engagement while in high school
  • Perceptions of labour market conditions
  • Perceptions of the cost of, and returns to, PSE
parental survey
Parental Survey
  • Expectation and aspirations for children
  • Education
  • Income
  • Family size
numeracy assessment
Numeracy Assessment
  • Measures how participants use math in every day life
  • Most compact way to control for differences in ability among students or schools
  • Marked inter-student variance that will interact with how they respond to experimental decisions
  • There is also a more important link - numeracy skill is the single most important determinant of both high school completion and PSE participation rates
experimental measures
Experimental Measures
  • Time Preferences
  • Risk Preferences
  • Education Choices
time preferences
Time Preferences
  • Binary Decisions organized in increasing reward
    • 6 rates
    • 4 Front End Delays
    • 2 investment or Wait times
  • 48 Decisions
risk preferences
Risk Preferences
  • All Graphical Representations
  • Two Basic Measures
    • Holt/Laury
      • 10 binary decisions
    • Eckel Grossman
      • 1 decsion chosen from SIX 50/50 gambles
    • (Binary Version of Eckel Grossman)
education choices
Education Choices
  • Basic Design:

cash v. Education financing

  • Use these decisions to distinguish pricing from form of financing
  • Control for
    • Size of cash alternative
    • Price of subsidy per $1 edu financing
    • Absolute value of edu subsidy
types of edu financing
Grants: $500 - $4000

Loans: $1000 - $4000

Income Contingent Loans

Hybrids (loans + Grants) $800 - $4000

Cash Alternatives: $25 - $700

Types of Edu Financing
aspiration levels and educational choices an experimental study

Aspiration levels and Educational Choices: an Experimental Study

LionelPage

Louis Lévy-Garboua

Claude Montmarquette

a sociological explanation for differences in educational choices
A sociological explanation for differences in educational choices
  • Sociologists (Boudon 1973) also invoke differences in aspiration levels among social classes: children from upper classes have higher aspirations than children from lower classes with identical abilities
  • Aspiration levels are reference-dependent and the natural reference for children is their parents’ level
  • Reaching a given level of education may be perceived as a failure in upper classes and a success in lower classes
prospect theory1
Prospect theory
  • Reference points play a central role in prospect theory (Kahneman and Tversky 1979)
  • The same outcome is framed or perceived as a GAIN if the reference is low, and as a LOSS if the reference is high
  • People are risk averse in the domain of gains and tend to be risk seeking in the domain of losses
  • Moreover, people are averse to losses
  • Page (2005a, 2005b) has, shown that the impact of aspiration levels on educational outcomes can be modeled with the notion of reference point from prospect theory.
why an experiment
Why an experiment?
  • On real-life data, it is difficult to control for many factors (e.g., abilities) and for the context of decision; and it is often impossible to observe causal variables
  • In our experiment, we observe and manipulate the reference point; and we are able to measure task-specific abilities so as to control for this important factor econometrically
  • We simulate experimentally the simplest schooling system in a context-free setting and compare the “human investments” of our experimental subjects in a GAIN treatment and in a LOSS treatment
slide60
The experiment is made of two treatments.
  • In one treatment, the outcomes are displayed as gains, framing a low reference point.
  • In the other treatment, the outcomes are presented as losses, framing a high reference point.
  • According to prospect theory, the framing of the monetary outcomes as losses should have two effects:
  • (i) The participants should be more likely to choose to continue at stages 9 and 12.
  • (ii) The participants should exert more effort to perform the task.
experimental design
Experimental Design
  • 15 stages grouped in 3 levels. Each stage involves solving a given number of anagrams. The first level contains the stages 1 to 9, the second level the stages 10 to 12 and the third level the stages 13 to 15.
  • At the end of each level, a participant must have solved two thirds of the anagrams to be allowed to pass to the next level.
  • The difficulty of the level increases according to the following criteria:

• The number of anagrams per stage increases with the level with a constant time limit of 8 minutes per stage. Specifically:

– 6 anagrams per stage for level 1,

– 9 anagrams per stage for level 2 and

– 12 anagrams per stage for level 3

• The length of anagrams increases on average. The structure of the experiment is represented in Figure 1. At the end of each level, the participant fails or passes, and correspondingly there are two possible outcomes in terms of monetary payments.

aspirations and performances
Aspirations and Performances
  • Proposition 1: Framing (LF) matters to continue education
  • Proposition 2: In LF participants should exert more effort
discussion
Discussion
  • Aspiration levels may play a major role in educational choices causing social inequalities in educational outcomes
  • Gender differential effect in LF not expected. If Emma if from a poor family, she would consider her outcome as positive if stopping at any intermediate level of education. If Ben is from a high social background, stopping at any intermediate level would be consider a failure
on table 4
On Table 4.....
  • Males from LF represent 55% of participants reaching the highest level vs 25% from chance alone
  • Males represent 78% of the highest achievers while they represent 55% of participants
  • Could the concentration of males in higher levels of education be due to the highest rate of success of males with high aspiration levels?
conclusion
Conclusion
  • We find that to frame outcomes as gains or losses in our experiment significantly changes the choices of the participants. Participants in the loss framing treatment chose more often to continue further in the stages of the experiment than participants in the gain framing treatment.
  • Concerning the effect of aspiration levels, the prediction stemming from prospect theory are only validated for males.
  • The framing of outcomes as losses, which was expected to increase the motivation of the participants, does so, but only for males.
individual responsibility in the funding of collective goods

Individual Responsibility in the Funding of Collective Goods

Louis Levy-Garboua (TEAM, University of Paris I)

Claude Montmarquette (CIRANO, University of Montreal)

Marie-Claire Villeval (CNRS)

1 motivation
1. Motivation

How to increase individual responsibility in voluntary contributions to funding collective goods?

Aim 1: Comparing the efficiency of taxation and rationing systems with respect to the private supply of public goods and the funding of deficits

  • Aim 2: Analyzing the effectiveness of individualizing the deficit handling by taxation or by rationing

A specific example: Public health insurance

a laboratory experiment
A laboratory experiment

A 2-stage experiment with a 2x2 design

  • Voluntary contributions to a common pool set by members of a group serve to compensate for the losses incurred by hit members
  • In case of a shortage of the common pool, 4 possible deficit

management modes: taxation / rationing

uniform/ individualized

2 theory
2. Theory

A two-stage collective goods game

  • Stage 1: Voluntary contribution to a common pool intended to compensate for the losses suffered by group members randomly afflicted in stage 2
  • Stage 2: Random selection of the victims and determination of the payoffs. Treatment of the possible deficit.

N =12; Number of victims: S =4 ; Probability of a loss

Individual endowment: Y = 100

Individual contribution:

: loss suffered by k, i.i.d.

: total losses in the group

uniform taxation
Uniform taxation

Individual tax = 1/N (deficit)

Taxation involves a deadweight loss

gi = 0 is a Nash equilibrium if

individualized taxation
Individualized taxation

The tax is individualized according to gi

Taxation involves a deadweight loss

Nash equilibrium: gi = L/N. Unique if all players are assumed similar.

Nash equilibrium = Optimum

uniform rationing
Uniform rationing

In case of a deficit, compensation is partial => payoff becomes uncertain. All the victims receive the same compensation

gi = 0 is a Nash equilibrium

individualized rationing
Individualized rationing

A victim’s compensation in stage 2 depends on his individual contribution in stage 1

2 conditions:

(i) A victim cannot be compensated for more than his loss

(ii) The total amount of compensations is always covered by the total amount of contributions

where ci(0

and with

slide86
u.c.

The Nash equilibrium is positive but below the optimum

to sum up
To sum up

Optimum Equilibrium

Uniform Taxation L/N 0 (provided

not too large)

Individualized Taxation L/N L/N (if )

Uniform Rationing L/N 0

Individualized Rationing L/N gi>0

3 experimental design
3. Experimental design

Regate software

24 sessions

(12 in BUL-C3E at CIRANO, Montreal, and 12 at GATE, Lyon)

288 participants from undergraduate classes in engineering and business schools

50 repetitions

90 minutes

A test of risk aversion at the end of the session (Can.$ 5 or €2 for sure or 50% chance of winning $11 or €5 and 50% chance of 0)

Average earnings: 35 Can.$ (23 €)

conclusion1
Conclusion
  • With respect to the relative efficiency of the diverse deficit coverage

institutions, the experimental results are compliant to the theoretical model

  • Uniform rationing is the worst system.
  • Uniform taxation, while encouraging free-riding just as much, is not much
  • more efficient since it imposes upon the community an extra tax burden.
  • Individualized taxation is the best deficit coverage model since
  • - it gives individuals a sense of responsibility
  • - it eliminates the sucker aversion
  • If taxation encourages cooperation (Andreoni, 1993), this is true for
  • individualized taxation but not for uniform taxation
the effects of perfect monitoring of matched income on tax compliance an experimental investigation

The effects of perfect monitoring of matched income on tax compliance: An experimental investigation

Cathleen Johnson,

David Masclet,

Claude Montmarquette

issues
Issues
  • Tax evasion is still an open question
    • There is more voluntary compliance than game theoretic models predict
    • There are more successful audits than principle agent models predict
    • Empirical evidence offers contradictory evidence on the effects of audit rates
motivation
Motivation
  • Typically, taxes are held for some time by businesses and paid to the government on a periodic basis
  • It is now possible for taxing authorities to receive sales taxes directly through financial institutions when payments are electronic
motivation1
Motivation
  • The IRS (1996) reports that income underreporting is the largest simple source of tax evasion. 72% in 1988
  • Would the implementation of an automated collection scheme increase tax revenue?
slide95
Note

Must consider that individuals may react differently to an substantial increase in audit rates:

Those who are relatively more risk averse will comply to maximize expected income.

Less risk averse will underreport even more to maintain current level of income

the basic experiment
The Basic Experiment
  • Subjects are instructed to play an unspecified number of periods
  • In each period Ss
    • Receive income (10-110)
    • Report income
    • Pay taxes on reported income
    • Experience an audit with some probability
    • Have complete history (private info)
income
Income
  • Two sources of income each period

Total = A + B

  • 3 types of income distribution
  • Player type and amount of income is private information
auditing
Auditing
  • Participants pay 40% tax on reported income
    • 20% probability of Audit on income for bottom half on income distribution
    • 10% probability of Audit on income in top half of income distribution
  • Penalty: unpaid tax + 50% and automatic audit on previous two periods.
a change in monitoring i
A change in monitoring (I)

I: A + B (21)

“A” will be perfectly revealed (6)

As promised (21)

a change in monitoring ii
A change in monitoring II

II: A + B (21)

“A” will be perfectly revealed

You can trade 6 A for 5 B (6)

As promised (21)

a change in monitoring
A change in monitoring
  • 12 sessions of 12 Ss each
  • All sessions implemented the change in monitoring (two treatments)
  • 6 sessions allowed for Ss to transfer income from source A to source B (II)
descriptive results
Descriptive results
  • Before announcement (basic phase), observed that audit rates did affect compliance.
    • Higher income, lower compliance rate
    • Overall compliance ≈ 70%
observations
Observations
  • Tax revenues increased for 80% monitored
  • Tax revenues decreased for every other group -- 15% total decrease
  • Announcement period:
    • Tax revenues decrease when individuals don’t see have an opportunity to transfer income
    • Remain the same when opportunity to shift to Souce B income (treatment II)
final thoughts
Final thoughts
  • Do we think this is what will happen in real life?
    • Other changes must happen in conjunction with this monitoring system or it may not work
    • Transition individuals to bank accounts
    • Reduce other costs of electronic payments
    • Tax decrease
    • Public goods aspect
    • About the difficulties of reducing fiscal fraud
conclusion g n rale
Conclusion Générale
  • L’EE aide a la compréhension des problèmes
  • Elle souligne des pistes de solutions
  • Elle permet d’influer sur les décideurs. Ces derniers ne sont jamais faciles à convaincre sur des bases théoriques, mais ils sont plus sensibles aux faits empiriques.
  • Pariez sur l’EE pour faire avancer les idées est un bon choix
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