A Laboratory Experiment on the Heuristic Switching Model
Transcript of A Laboratory Experiment on the Heuristic Switching Model
A Laboratory Experiment on the Heuristic Switching Model
A Laboratory Experiment on theHeuristic Switching Model
Mikhail Anufrieva Aleksei Chernulicha Jan Tuinstrab
a University of Technology Sydneyb University of Amsterdam
Symposium for Experimental EconomicsDongbei University of Finance and Economics (DUFE)
29 October 2017
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A Laboratory Experiment on the Heuristic Switching Model
SummaryExperiment focusing on one (of the two) keymechanisms of Heuristic Switching Models and ...
... testing implications of Brock-Hommes (ECMA 1997,JEDC 1998) model
Consistently with the model: high information cost ofrational rule cause instability
Evidence of endogenous change in switching
... consistent with Intensity of Choice parameter reactingon predictability of past returns ...
... leading to “moderately complex” dynamics
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A Laboratory Experiment on the Heuristic Switching Model
Outline
1 Introduction
2 Experiment
3 Dynamics of the Stylized HSM and Hypotheses
4 Results of the Experiment
5 High (Large and Long) Treatment
6 Conclusion
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A Laboratory Experiment on the Heuristic Switching Model
Introduction
Plan
1 Introduction
2 Experiment
3 Dynamics of the Stylized HSM and Hypotheses
4 Results of the Experiment
5 High (Large and Long) Treatment
6 Conclusion
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A Laboratory Experiment on the Heuristic Switching Model
Introduction
Expectations in Economic Theoryeconomy is an expectation feedback system
expectations a�ect our decisions and realizationsexpectations may be a�ected by past experience
expectations play the key role in most economic models30s-60s naive and adaptive expectations70s-90s rational expectations
90s models of learning and bounded rationalityadaptive learning (OLS-learning)bayesian and belief-based learningreinforcement learning
2000s- heterogeneous expectations (HeterogeneousAgent Models)
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A Laboratory Experiment on the Heuristic Switching Model
Introduction
Example: Model of Financial Marketdemand for the long-lived asset of a myopic MV trader
Dh(pt) =Eh,t[pt+1 + yt+1] − (1 + r)pt
a Vh,t[pt+1 + yt+1]
solve market clearing at time t, find equilibrium∑hDh(pt) = 0 ; pt =
11 + r
∑hEh,t[pt+1 + yt+1]
rational (homogeneous) expectations
pt =1
1 + rEt[pt+1+yt+1] ; (for i.i.d. dividends) pf =
yr
heterogeneous expectations
pt =1
1 + r
∑h
Eh,t
[1
1 + r
∑h′
Eh′,t+1[pt+2 + yt+2] + yt+1
]6 / 53
A Laboratory Experiment on the Heuristic Switching Model
Introduction
Example (ctd): Heterogeneous Agent Modelthere are two types of investors
fundamentalists, Ef ,t [pt+1] = pf + v(pf − pt−1)chartists, Ec,t [pt+1] = pt−1 + g(pt−1 − pt−2) with g > 0
evolution of price
pt =1
1 + r
(nf ,t Ef ,t[pt+1] + nc,t Ec,t[pt+1]
)+
y1 + r
evolution of fractions
nf ,t+1 =exp [βπf ,t]
exp [βπf ,t] + exp [βπc,t]
profits πf ,t and πc,t are computed as their holdings timesreturn pt + yt − (1 + r)pt−1 and known to everybody
fundamentalists pay fixed cost C > 07 / 53
A Laboratory Experiment on the Heuristic Switching Model
Introduction
Example (ctd): Simulation
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A Laboratory Experiment on the Heuristic Switching Model
Introduction
HAMs and their Empirical ValidationHAMs assume several expectational rules (a�ecting tradingbehavior); these rules get reinforced from their past profit.Do the data support this theory?Empirical Studies
Branch (2004), Boswijk, Hommes and Manzan (2007),Goldbaum and Mizrach (2008), De Jong, Verschoor, andZwinkels (2009), Kouwenberg and Zwinkels (2010),Franke and Westerho� (2011), Chiarella, He andZwinkels (2014)
Experimental StudiesHommes et al (2005, 2008), Heemeijer et al (2009),Anufriev and Hommes (2012), Bao et al (2012), Pfajfarand Žakelj (2014), Assenza et al (2015), Anufriev, Bao,Tuinstra (2016, JEBO) 9 / 53
A Laboratory Experiment on the Heuristic Switching Model
Introduction
Heuristic Switching ModelsRational Expectation Hypothesis: Restrictivetheoretical assumptions and Limited empirical validity.
Heterogeneous Agent Models (HAMs):1 agents use behavioral decision rules (“forecasting
heuristics”)2 agents switch between rules based on their past
performances (Brock and Hommes, 1997).
Applications: Financial markets (endogenous bubblesand crashes and a lot of “stylized facts”),Macroeconomics (persistence of inflation, di�erent policyimplications).
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A Laboratory Experiment on the Heuristic Switching Model
Introduction
Brock-Hommes model (ECMA, 1997; JEDC, 1998)Setup
Supply/Demand-driven market where participants mustform expectations about future priceThe equilibrium is stable under costly Rationalexpectations and unstable under free Naive expectationsDiscrete choice is based on past profits
PredictionIf cost of RE is high, prices exhibit bubble/crash pa�erns
MechanismNear equilibrium two heuristics give similar forecastsand, due to fix cost of RE, majority uses naive ruleDynamics diverge and naive expectations get less preciseEventually majority switches to Rational expectationsand price returns towards equilibrium 11 / 53
A Laboratory Experiment on the Heuristic Switching Model
Introduction
Role of Lab ExperimentsHAMs are empirically successful, tractable, intuitive......but the dynamics depends on the chosen heuristics andtheir cost and also parameters of switching.
Experiments with paid human subjects allow to1 test assumptions and implications2 pin down relevant heuristics (LtF)3 estimate parameters of switching
in a controlled environment.
Switching ExperimentsAnufriev, Bao, and Tuinstra (JEBO, 2016) tested switchingbetween 2, 3 or 4 heuristics on exogenous dataThis paper: binary choice on endogenous data
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A Laboratory Experiment on the Heuristic Switching Model
Introduction
General setup of switching modelsagents’ choices are distributed over H di�erent heuristics.past payo�s of heuristics are known:
πht−1, π
ht−2, . . . , π
ht−`, . . .
fraction of agents using heuristic h at time t, is given bydiscrete choice model (Manski and McFadden, 1981)
nh,t =exp [αh + βπh,t−1]∑Hk=1 exp [αk + βπk,t−1]
,
where β > 0 is the Intensity of Choice and αh ≡ 0
Anufriev, Bao, and Tuinstra (JEBO, 2016) found that:(i) intensity of choice is not the same across treatments,but depends on past predictability of profits;(ii) model with predisposition (α1 > 0) provides be�er fit
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A Laboratory Experiment on the Heuristic Switching Model
Introduction
General setup of switching modelsagents’ choices are distributed over H di�erent heuristics.past payo�s of heuristics are known:
πht−1, π
ht−2, . . . , π
ht−`, . . .
fraction of agents using heuristic h at time t, is given bydiscrete choice model (Manski and McFadden, 1981)
nh,t =exp [αh + βπh,t−1]∑Hk=1 exp [αk + βπk,t−1]
,
where β > 0 is the Intensity of Choice and αh ≡ 0Anufriev, Bao, and Tuinstra (JEBO, 2016) found that:(i) intensity of choice is not the same across treatments,but depends on past predictability of profits;(ii) model with predisposition (α1 > 0) provides be�er fit
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A Laboratory Experiment on the Heuristic Switching Model
Introduction
Other Studies for HSMs Estimation andCalibration
on financial data: Boswijk, Hommes and Manzan (JEDC,2007), Goldbaum and Mizrach (JEDC, 2008), Chiarella,He and Zwinkels (JEBO, 2014), Cornea-Madeira,Hommes, and Massaro (JBES, 2017)
on survey data: Branch (EJ, 2004), Goldbaum andZwinkels (JEBO, 2014)
on experimental data: Hommes (JEDC, 2011), Anufrievand Hommes (AEJ-Micro, 2012), Anufriev, Hommes andPhilipse (JEE, 2013)
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A Laboratory Experiment on the Heuristic Switching Model
Introduction
Objectives of the experiment1 Verify if aggregate switching behavior is well described
by the discrete choice model;
2 Provide estimations of the Intensity of Choice parameterfor calibration purposes;
3 Study possible e�ects of endogeneity in profits onswitching (cf., Anufriev, Bao, Tuinstra, JEBO, 2016)
4 Test a prediction of Brock-Hommes (E, 1997; JEDC, 1998)model about the e�ects of information cost di�erencebetween heuristics (e.g., rational expectations vs. naive)
Low: stable dynamicsHigh: locally unstable but bounded (bubbles and
crashes) 15 / 53
A Laboratory Experiment on the Heuristic Switching Model
Experiment
Plan
1 Introduction
2 Experiment
3 Dynamics of the Stylized HSM and Hypotheses
4 Results of the Experiment
5 High (Large and Long) Treatment
6 Conclusion
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A Laboratory Experiment on the Heuristic Switching Model
Experiment
Screen
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A Laboratory Experiment on the Heuristic Switching Model
Experiment
ExperimentIndividual discrete choice experiment with group e�ect
10 Participants:choose between alternatives A and B during 40 periods inone Block and then during 40 periods in another Block
are informed that the profits of alternatives depend ontheir and other participants’ choices
are not informed about the functional forms of profitgenerating processes
are shown the history of past profits (graph and table)
Additional Sessions: 35 participants, 60 periods18 / 53
A Laboratory Experiment on the Heuristic Switching Model
Experiment
DGP: Stylized version of the BH modelEndogenous Variables:
πA,t profit of “rational” (stabilizing but costly) heuristicπB,t profit of “naive” (cheap but destabilizing) heuristicxt “deviation of price from REE steady state”nB,t share of “naive” heuristic’s users, 1− nB,t = nA,t
State Variable Dynamics and Profits of Heuristics
xt = λnB,txt−1 + εt
πA,t = w + γAx2t , πB,t = W − γBx2twith λ = 2.1, γA + γB = 1, w < W , εt ∼ N (0, 0.1)
Exogenous Variable:W − w = C cost di�erenceC > 0 means that “rational” heuristic is more costly
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A Laboratory Experiment on the Heuristic Switching Model
Experiment
DGP: Stylized version of the BH modelEndogenous Variables:
πA,t profit of “rational” (stabilizing but costly) heuristicπB,t profit of “naive” (cheap but destabilizing) heuristicxt “deviation of price from REE steady state”nB,t share of “naive” heuristic’s users, 1− nB,t = nA,t
State Variable Dynamics and Profits of Heuristics
xt = λnB,txt−1 + εt
πA,t = w + γAx2t , πB,t = W − γBx2twith λ = 2.1, γA + γB = 1, w < W , εt ∼ N (0, 0.1)Exogenous Variable:
W − w = C cost di�erenceC > 0 means that “rational” heuristic is more costly
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A Laboratory Experiment on the Heuristic Switching Model
Experiment
Experiment Design and ParametrizationState variable dynamics
xt = 2.1nB,txt−1 + εt, εt ∼ N (0, 0.1), x0 = 0Two Blocks of 40 decision periods in each
High: C = 8πA,t = 1 + 0.6x2t , πB,t = 9− 0.4x2t
Low: C = 1πA,t = 4.95 + 0.6x2t , πB,t = 5.05− 0.4x2t
Two treatments with 4 sessions each and rematchingparticipants by the groups of 10
High block to Low blockLow block to High block
2 extra sessions for High Treatment (N = 35, T = 60)20 / 53
A Laboratory Experiment on the Heuristic Switching Model
Dynamics of the Stylized HSM and Hypotheses
Plan
1 Introduction
2 Experiment
3 Dynamics of the Stylized HSM and Hypotheses
4 Results of the Experiment
5 High (Large and Long) Treatment
6 Conclusion
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A Laboratory Experiment on the Heuristic Switching Model
Dynamics of the Stylized HSM and Hypotheses
Dynamics of the Stylized HSMAssuming discrete choice model with predisposition
Probability to choose B =1
1 + eα+β(πA,t−1−πB,t−1)
and large population (nB,t = Probability to choose B)
the state variable evolves as
xt =λxt−1
1 + eα+β(x2t−1−(W−w))
+ εt =2.1xt−1
1 + eα+β(x2t−1−C)
+ εt
In the experiment we vary the cost di�erence:High Block : C = 8Low Block : C = 0.1
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A Laboratory Experiment on the Heuristic Switching Model
Dynamics of the Stylized HSM and Hypotheses
Properties of the Model Dynamics
xt = λxt−1
1 + exp[α + β(x2t−1 − C)]
x∗ = 0 is a steady state for all parameter values. Thissteady state is unique and globally stable for λ < 1.For λ > 0 the system undergoes a pitchfork bifurcationwhen λ = 1 + exp(α− βC).At the moment of the bifurcation two non-zero steadystates, x+ > 0 and x− < 0, are created, withcorresponding steady state fraction 1/λ.For λ < 0 the system undergoes a period doublingbifurcation when −λ = 1 + exp(α− βC).At the moment of the bifurcation a 2-cycle is created,with corresponding steady state fraction −1/λ.
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A Laboratory Experiment on the Heuristic Switching Model
Dynamics of the Stylized HSM and Hypotheses
Bifurcation Diagrams: C = 8 vs C = 0.1Let λ = 2.1:
0.0 0.2 0.4 0.6 0.8 1.0
-0.4
-0.2
0.0
0.2
0.4
β
α
High Information Cost
0 5 10 15 20
-0.4
-0.2
0.0
0.2
0.4
β
α
Low Information Cost
Red: the zero steady state is stableBlue: the non-zero steady states are stable
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A Laboratory Experiment on the Heuristic Switching Model
Dynamics of the Stylized HSM and Hypotheses
Bifurcation Diagrams: C = 8 vs C = 0.1Let λ = 2.1:
α = 0.4 α = 0 α = −0.425 / 53
A Laboratory Experiment on the Heuristic Switching Model
Dynamics of the Stylized HSM and Hypotheses
Simulation: C = 8 vs C = 0.1Let λ = 2.1, α = 0, β = 5:
0 5 10 15 20 25 30 35 40time period
-5
-4
-3
-2
-1
0
1
2
3
4
5
stat
e va
riabl
e, x
parametrization of High blocks
0 5 10 15 20 25 30 35 40time period
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
stat
e va
riabl
e, x
parametrization of Low blocks
0 5 10 15 20 25 30 35 40time period
0
0.2
0.4
0.6
0.8
1
frac
tion
of B
cho
ice
parametrization of High blocks
0 5 10 15 20 25 30 35 40time period
0
0.2
0.4
0.6
0.8
1
frac
tion
of B
cho
ice
parametrization of Low blocks
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A Laboratory Experiment on the Heuristic Switching Model
Dynamics of the Stylized HSM and Hypotheses
Hypotheses
H1. There is a di�erence in volatility of both nB,t andxt between the High blocks and the Low blocks.
H2. The endogenous variable nB,t can be described bya discrete choice model with one lag and apredisposition e�ect.
H3. There is no di�erence between the discretechoice models estimated for High and for Lowblocks. In particular, the Intensity of Choiceparameter is the same.
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A Laboratory Experiment on the Heuristic Switching Model
Results of the Experiment
Plan
1 Introduction
2 Experiment
3 Dynamics of the Stylized HSM and Hypotheses
4 Results of the Experiment
5 High (Large and Long) Treatment
6 Conclusion
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A Laboratory Experiment on the Heuristic Switching Model
Results of the Experiment
Fraction of B-choices: High-Low Treatment I
0 5 10 15 20 25 30 35 40time period
0
0.2
0.4
0.6
0.8
1
frac
tion
of B
cho
ice
High: Session 1, group 1
0 5 10 15 20 25 30 35 40time period
0
0.2
0.4
0.6
0.8
1
frac
tion
of B
cho
ice
Low: Session 1, group 1
0 5 10 15 20 25 30 35 40time period
0
0.2
0.4
0.6
0.8
1
frac
tion
of B
cho
ice
High: Session 1, group 2
0 5 10 15 20 25 30 35 40time period
0
0.2
0.4
0.6
0.8
1
frac
tion
of B
cho
ice
Low: Session 1, group 2
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A Laboratory Experiment on the Heuristic Switching Model
Results of the Experiment
Fraction of B-choices: High-Low Treatment II
0 5 10 15 20 25 30 35 40time period
0
0.2
0.4
0.6
0.8
1
frac
tion
of B
cho
ice
High: Session 3, group 1
0 5 10 15 20 25 30 35 40time period
0
0.2
0.4
0.6
0.8
1
frac
tion
of B
cho
ice
Low: Session 3, group 1
0 5 10 15 20 25 30 35 40time period
0
0.2
0.4
0.6
0.8
1
frac
tion
of B
cho
ice
High: Session 3, group 2
0 5 10 15 20 25 30 35 40time period
0
0.2
0.4
0.6
0.8
1
frac
tion
of B
cho
ice
Low: Session 3, group 2
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A Laboratory Experiment on the Heuristic Switching Model
Results of the Experiment
Fraction of B-choices: Low-High Treatment I
0 5 10 15 20 25 30 35 40time period
0
0.2
0.4
0.6
0.8
1
frac
tion
of B
cho
ice
Low: Session 2, group 1
0 5 10 15 20 25 30 35 40time period
0
0.2
0.4
0.6
0.8
1
frac
tion
of B
cho
ice
High: Session 2, group 1
0 5 10 15 20 25 30 35 40time period
0
0.2
0.4
0.6
0.8
1
frac
tion
of B
cho
ice
Low: Session 2, group 2
0 5 10 15 20 25 30 35 40time period
0
0.2
0.4
0.6
0.8
1
frac
tion
of B
cho
ice
High: Session 2, group 2
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A Laboratory Experiment on the Heuristic Switching Model
Results of the Experiment
Fraction of B-choices: Low-High Treatment II
0 5 10 15 20 25 30 35 40time period
0
0.2
0.4
0.6
0.8
1
frac
tion
of B
cho
ice
Low: Session 4, group 1
0 5 10 15 20 25 30 35 40time period
0
0.2
0.4
0.6
0.8
1
frac
tion
of B
cho
ice
High: Session 4, group 1
0 5 10 15 20 25 30 35 40time period
0
0.2
0.4
0.6
0.8
1
frac
tion
of B
cho
ice
Low: Session 4, group 2
0 5 10 15 20 25 30 35 40time period
0
0.2
0.4
0.6
0.8
1
frac
tion
of B
cho
ice
High: Session 4, group 2
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A Laboratory Experiment on the Heuristic Switching Model
Results of the Experiment
Histograms of B-choices
High: All groups
0 0.2 0.4 0.6 0.8 1
fraction of B choice
0
10
20
30
40
50
freq
uenc
y
Low: All groups
0 0.2 0.4 0.6 0.8 1
fraction of B choice
0
10
20
30
40
50
freq
uenc
y
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A Laboratory Experiment on the Heuristic Switching Model
Results of the Experiment
State Variable: High - Low Treatment I
0 5 10 15 20 25 30 35 40time period
0
1
2
3
4
5
6
7
8
9
stat
e va
riabl
e, x
Session 1
High: group 1
High: group 2
Low: group 1
Low: group 2
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A Laboratory Experiment on the Heuristic Switching Model
Results of the Experiment
State Variable: High - Low Treatment II
0 5 10 15 20 25 30 35 40time period
0
1
2
3
4
5
6
7
8
9
stat
e va
riabl
e, x
Session 3
High: group 1
High: group 2
Low: group 1
Low: group 2
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A Laboratory Experiment on the Heuristic Switching Model
Results of the Experiment
State Variable: Low - High Treatment I
0 5 10 15 20 25 30 35 40time period
0
1
2
3
4
5
6
7
8
9
stat
e va
riabl
e, x
Session 2
High: group 1
High: group 2
Low: group 1
Low: group 2
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A Laboratory Experiment on the Heuristic Switching Model
Results of the Experiment
State Variable: Low - High Treatment II
0 5 10 15 20 25 30 35 40time period
0
1
2
3
4
5
6
7
8
9
stat
e va
riabl
e, x
Session 4
High: group 1
High: group 2
Low: group 1
Low: group 2
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A Laboratory Experiment on the Heuristic Switching Model
Results of the Experiment
Descriptive statistics
Fraction of B-choices, nB State Variable, xData Mean Std. Dev. Mean Std. Dev.
Session 1. Group 1 0.58 0.27 2.43 1.52Session 1. Group 2 0.61 0.25 2.26 1.52
High Session 2. Group 1 0.60 0.27 2.51 1.47Session 2. Group 2 0.58 0.28 2.39 1.27...
......
......
All groups 0.59 0.26 2.43 1.52
Session 1. Group 1 0.56 0.23 0.26 0.22Session 1. Group 2 0.51 0.23 0.26 0.24
Low Session 2. Group 1 0.55 0.24 0.17 0.21Session 2. Group 2 0.56 0.24 0.13 0.28...
......
......
All groups 0.54 0.24 0.20 0.2438 / 53
A Laboratory Experiment on the Heuristic Switching Model
Results of the Experiment
Discrete Choice Model
IoC Predisposition Zero SS Non-Zero SS
Data Beta S.E. Alpha S.E. (x∗, n∗) f ′(x∗) (x+, n+) f ′(x+)
Session 1. Group 1 0.08 0.01 0.31 0.11 (0,0.58) 1.22 (2.31,0.48) 0.55Session 1. Group 2 0.12 0.02 0.38 0.11 (0,0.64) 1.35 (2.37,0.48) 0.29
High Session 2. Group 1 0.12 0.02 0.35 0.11 (0,0.65) 1.36 (2.42,0.48) 0.26Session 2. Group 2 0.17 0.02 0.28 0.11 (0,0.75) 1.57 (2.63,0.48) -0.23...
......
......
......
......
All groups 0.12 0.01 0.25 0.04
Session 1. Group 1 3.35 0.84 0.26 0.11 (0,0.52) 1.09 (0.23,0.48) 0.82Session 1. Group 2 5.24 0.93 0.09 0.11 (0,0.61) 1.27 (0.32,0.48) 0.45
Low Session 2. Group 1 11.35 1.66 -0.17 0.13 (0,0.79) 1.65 (0.35,0.48) -0.47Session 2. Group 2 8.67 1.47 0.10 0.11 (0,0.68) 1.43 (0.32,0.48) 0.10...
......
......
......
......
All groups 5.71 0.42 0.11 0.04
Table: Estimations of the DCM with one lag and predisposition.
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A Laboratory Experiment on the Heuristic Switching Model
Results of the Experiment
Estimations on the Bifurcation diagram
0.0 0.2 0.4 0.6 0.8 1.0
-0.4
-0.2
0.0
0.2
0.4
β
α
High Information Cost
0 5 10 15 20
-0.4
-0.2
0.0
0.2
0.4
β
α
Low Information Cost
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A Laboratory Experiment on the Heuristic Switching Model
High (Large and Long) Treatment
Plan
1 Introduction
2 Experiment
3 Dynamics of the Stylized HSM and Hypotheses
4 Results of the Experiment
5 High (Large and Long) Treatment
6 Conclusion
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A Laboratory Experiment on the Heuristic Switching Model
High (Large and Long) Treatment
Fraction of B-choices: Large/Long High T
0 10 20 30 40 50 60time period
0
0.2
0.4
0.6
0.8
1
frac
tion
of B
cho
ice
High: Large - Long, group 1
0 10 20 30 40 50 60time period
0
0.2
0.4
0.6
0.8
1
frac
tion
of B
cho
ice
High: Large - Long, group 2
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A Laboratory Experiment on the Heuristic Switching Model
High (Large and Long) Treatment
State Variable: Large and Long High Treatment
0 10 20 30 40 50 60time period
0
1
2
3
4
5
6
7
8
9
stat
e va
riabl
e, x
Large - Long Sessions
Session 1
Session 2
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A Laboratory Experiment on the Heuristic Switching Model
High (Large and Long) Treatment
Estimations on the Bifurcation diagram
0.0 0.2 0.4 0.6 0.8 1.0
-0.4
-0.2
0.0
0.2
0.4
β
α
High Information Cost
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A Laboratory Experiment on the Heuristic Switching Model
Conclusion
Plan
1 Introduction
2 Experiment
3 Dynamics of the Stylized HSM and Hypotheses
4 Results of the Experiment
5 High (Large and Long) Treatment
6 Conclusion
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A Laboratory Experiment on the Heuristic Switching Model
Conclusion
Hypotheses and ResultsH1. There is a di�erence in volatility of both nB,t and
xt between the High blocks and the Low blocks.
Confirmed, especially for xt .
H2. The endogenous variable nB,t can be described bya discrete choice model with one lag and apredisposition e�ect.
Confirmed.
H3. There is no di�erence between the discrete choicemodels estimated for High and for Low blocks.
There is a di�erence in values of parameters.
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A Laboratory Experiment on the Heuristic Switching Model
Conclusion
Conclusion1 E�ect of information cost in Brock-Hommes model is
confirmed.
2 At the same time, participants adapt their choice to theenvironment they are in.
They become less sensitive to past profit di�erences inless stable environment.
As a result aggregate dynamics become only moderatelycomplex: e.g., asymmetric equilibrium or 2-cycle.
3 Theoretical literature of HSM may need to take it onboard and endogenize the Intensity of Choice.
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A Laboratory Experiment on the Heuristic Switching Model
Conclusion
THANK YOU!
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A Laboratory Experiment on the Heuristic Switching Model
Experimental results
Plan
7 Experimental results
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A Laboratory Experiment on the Heuristic Switching Model
Experimental results
Profits in High blocks
Figure: Profits dynamics 50 / 53
A Laboratory Experiment on the Heuristic Switching Model
Experimental results
Profits in Low blocks
Figure: Profits dynamics 51 / 53
A Laboratory Experiment on the Heuristic Switching Model
Experimental results
Table: Estimations of the discrete choice model with two lags andpredisposition.
Predisposition IoC IoCData Alpha S.E. Beta S.E. Beta2 S.E.
Session 1. Group 1 0.33 0.11 0.08 0.02 0.02 0.01Session 1. Group 2 0.40 0.11 0.12 0.02 0.02 0.02
High Session 2. Group 1 0.35 0.11 0.11 0.02 -0.02 0.02Session 2. Group 2 0.28 0.12 0.17 0.02 0.01 0.02
all groups and sessions 0.33 0.06 0.12 0.01 0.00 0.01
Session 1. Group 1 0.25 0.11 3.19 0.88 0.57 0.57Session 1. Group 2 0.04 0.11 5.20 0.97 -0.76 0.80
Low Session 2. Group 1 -0.17 0.13 11.35 1.73 1.13 1.31Session 2. Group 2 0.12 0.12 8.91 1.51 1.74 0.88
all groups and sessions 0.12 0.06 6.21 0.62 0.56 0.39
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A Laboratory Experiment on the Heuristic Switching Model
Experimental results
Table: Estimations of the discrete choice model with three lags andpredisposition.
Predisposition IoC IoC IoCData Alpha S.E. Beta S.E. Beta2 S.E. Beta3 S.E.
Session 1. Group 1 0.31 0.11 0.07 0.02 0.02 0.02 -0.01 0.01Session 1. Group 2 0.40 0.12 0.11 0.02 0.01 0.02 0.01 0.02
High Session 2. Group 1 0.32 0.11 0.11 0.02 -0.03 0.02 0.00 0.01Session 2. Group 2 0.26 0.12 0.16 0.02 0.01 0.02 -0.02 0.02
all groups and sessions 0.31 0.06 0.11 0.01 0.00 0.01 0.00 0.01
Session 1. Group 1 0.28 0.11 3.19 0.84 0.09 0.67 0.92 0.60Session 1. Group 2 -0.01 0.11 5.21 0.96 -0.85 0.83 -0.77 0.82
Low Session 2. Group 1 -0.12 0.13 11.45 1.73 1.64 1.36 -1.33 1.50Session 2. Group 2 0.17 0.12 9.14 1.53 2.11 0.89 -0.11 0.98
all groups and sessions 0.13 0.06 6.27 0.62 0.62 0.42 0.01 0.38
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