Committee Processes as Information Aggregation Mechanisms: Process Design and Experimental Results...
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Committee Processes as Information Aggregation Mechanisms: Process Design
and Experimental Results
Morgan H. Llewellyn
Charles R. Plott
California Institute of Technology
Presented at the Lee Center Workshop May 2006
MARKETS AND PRICES ARE KNOWN TO BE INFORMATION VEHICLES
Information held by insiders CAN get transmitted to outsiders.
CAN COMMITTEE PROCESSES, PROPOSALS AND VOTING BE INFORMATION VEHICLES?
Those who care have the right to vote but the information is held by special interests with no right to vote.
WHAT TYPE OF PROCESS CAN GET THE INFORMATION FROM THE INSIDERS TO THE
OUTSIDERS?
EVENTS
Information Aggregation Mechanisms
As the event unfolds signals and indicators are dispersed to different people. No isolated, individual signal is strong.
PREDICTION ABOUT EVENTS
SOMETHING HAPPENING?
Information in the signals differs from the information in humans. Filtered by human observation, it exists subjectively as vague ideas,
intuition and hunches.
A B C D E F
CCCCC
C
..
....
..
....
..
C
..
..
..
C
event drawn it is C
individual signals drawn conditional on event C
signals dispersed to separate individuals
10 20 30 40 50 60 70
30
20
10
50
40
Alternatives: Points on the Chalkboard
$125
$90
$75
$20$1
Committees and electionsOptions and incentives
18020 140 16080 100 120
140
40 60
60
80
120
20
40
conflict and incentives
Committees and electionsOptions and incentives
18020 140 16080 100 120
140
40 60
60
80
120
20
40
Rules and Institutions
Equilibrium and cooperative game models (e.g the core) tend to be the best models of the outcome
INFORMATION VARIABLE:
•DECISIONS ARE MADE BY THOSE WHO CARE (COMMITTEE MEMBERS WHO VOTE) BUT DO NOT KNOW THE STATE
•THE STATE IS KNOWN BY THOSE WHO CARE BUT CANNOT VOTE
•INFORMED AGENTS HAVE A DYADIC, EQUILIBIRUM CONFORMING RELATIONSHIP.
Base Parameters (signal is 0,0)
0
10
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90
0 20 40 60 80 100
1
2
4
5
3
Base Preferences
0
1020
3040
5060
7080
90
0 20 40 60 80 100
Dyadic
Equilibrium Conforming
Linear Influence Hypothesis
Individuals are informed about the location of their own maximum given the state relative to
the optimum of the insiders (who have information about the state).
0
20
40
60
80
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120
140
0 50 100 150 200
RESULTS
The institutional design was successful: Information Aggregation takes place
The general informational environment is important
We have some understanding of why•The linear Influence Hypothesis works well
• The behaviors of the insiders have expected features
• The initial recommendations of insiders is not the only source of information
The institutional design was successful: Information Aggregation takes place
The general informational environment is important
NO INFORMATION FINAL 060507
0
20
40
60
80
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120
140
0 20 40 60 80 100 120 140
NO INFORMATION 060507 finalY-EQY
-10
-5
0
5
10
-10 -5 0 5 10
FULL STATE INFORMATION 060507 final-EQ
-10
-5
0
5
10
-10 -5 0 5 10
Full Information 060507 final and EQ
0
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40
60
80
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120
140
0 50 100 150
final
EQY
Polar Cases: No Information About State
Polar Cases: Full Information About the State
060128 Equilibrium, Final Decisions and Deviation of Decisions from EquilibriumNo State Revelation
-20
0
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40
60
80
100
-20 0 20 40 60 80 100
060129 final decision, equilibrium and deviations of final decision from equilibrium No State Revelation
-20
0
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100
-40 -20 0 20 40 60 80 100
060114 Outcome and EquilibriaAfter Period State Revelation
-20
0
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-20 0 20 40 60 80 100
060125 final decision, equilibrium and deviation of final decision from equilibrium
No State Revelation
-20
0
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40
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100
-20 0 20 40 60 80 100
Distance from Fully Informed Equilibrium: Feedback
-30
-20
-10
0
10
20
30
-30 -20 -10 0 10 20 30
COMMITTEE NEVER LEARNS THE TRUTH
COMMITTEE LEARNS TRUTH AFTER EVERY DECISION
Distance from Fully Informed Equilibrium: No Feedback
-30
-20
-10
0
10
20
30
-30 -20 -10 0 10 20 30
Information Aggregation Does not Deteriorate Over Time
Euclidean Distance Between Final Decision and Fully Informed Equilibrium by Period: All
Observationsy = -0.06x + 8.68*
0
10
20
30
0 2 4 6 8 10 12 14
Period
Eu
clid
ean
D
ista
nce
COMPETITION AND STRATEGIES OF INSIDERS: Shaped by the institutions
•Strategic exaggerations and misrepresentations by insiders can be observed.
•Equilibrium conforming conflicts reduce the advantage of collusion among insiders.
•The insider proposals contain information and it is used. The linear inference model receives support.
SOURCES OF INFORMATION
LINEAR INFLUENCE MODELInsider recommendations are potential sources of information
Feedback
.51,.51
No Feedback
.51, .48
0
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0 20 40 60 80 100
The distance between insider recommendations is increasing in periods for feedback, but the distance is not statistically significant for
the periods with no feedback
Euclidean Distance Between A&B's Initial Recommendations By Period: Feedback
y = 1.83*x + 12.73*
0102030405060
0 2 4 6 8 10 12 14
Period
Eucl
idea
n D
ista
nce
Initial proposals A and B
Euclidean Distance Between A&B's Initial Recommendations By Period: No Feedback
y = 0.63x + 24.23*
0
20
40
60
80
100
0 2 4 6 8 10 12 14
Period
Eucl
idea
n D
ista
nce
The mechanism contains sources of information in addition to the initial proposals by the insiders
Euclidean Distance Between A&B's Recommendation and Number Amendments in a Period: Feedback All
Periodsy = 0.43x + 21.05*
0
20
40
60
80
100
0 2 4 6 8 10 12 14 16
Euclidean Distance Between A&B's Recommendation and Amendments in a Period: Feedback Periods 4-14
y = 1.11*x + 18.91*
0
20
40
60
80
100
0 2 4 6 8 10 12 14 16
Lack of trust in initial recommendations causes people to look for other sources of information such as amendments to proposals.
Euclidean Distance Between A&B's Recommendations by Number of Proposals: No Feedback
y = 0.60x + 25.02*
0
20
40
60
80
100
0 2 4 6 8 10 12 14 16
Euclidean Distance Between A&B's Recommendation by Number of Proposals: No Feedback Periods 4-13
y = 0.42x + 27.94*
0
20
40
60
80
100
0 2 4 6 8 10 12 14 16
Accuracy improves with truthfulness of insiders and with
experience
Decision distancei = distance between a&b recs + period + constant
• Conclusions: distance from equilibrium increases with the distance between A & B’s recommendations grow, but the amendment process possesses conveys information which decreases error
Decision Distance Coefficient Standard deviation t-statistc
Distance between
A &B
.24 .07 3.52
Period -.45 .23 -1.98
Constant 3.67 1.58 2.32
feedback environment
Individual voting behavior evolves away from a state of completely uniformed
Ratio of Mistakes to Correct Votes by Amendment Assuming Sincere Voting
0
0.2
0.4
0.6
0.8
1
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Fully Informed
completely uninformed
SPEICAL COMMITTEE ORGANIZATION FACILITATES INFORMATION AGGREGATION: INFORMATION SEEPS IN EVEN WHEN HELD ONLY BY SELF INTERESTED PARTIES.
DYADIC, EQUILIBRIUM CONFORMING CONFLECTS ARE CENTRAL: CLASSICAL MODELS OF COMMITTEE DECISIONS APPLY
THE SUCCESS OF THE MECHANISM DEPENDS UPON THE BACKGROUND INFORMATION ENVIRONMENT
THE END
ADDITIONAL OBSERVATIONS
New Proposals Are Closer to the Fully Informed Equilibrium than the Previous Proposal
Feedback Environment
Distance between
Proposal and Fully Informed Equilibrium
Coefficient Standard deviation t-statistc
Proposal number in the period
-.46 .14 -3.16
Constant 12.12 .76 15.9
No Feedback Environment
Distance between
Proposal and Fully Informed Equilibrium
Coefficient Standard deviation t-statistc
Proposal number in the period
-.55 .16 -3.37
Constant 14.58 .77 18.92
Total PivotalPivotal to Total Mistakes by Amendment Under No Information Sincere Voting: No Feedback
0
50
100
150
1 2 3 4 5 6 7 8 9 10 11 12 13 14
Amendment Number
Pivotal to Total Mistakes by Amendment Under No Information Sincere Voting: Feedback
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50
100
150
1 2 3 4 5 6 7 8 9 10 11 12 13 14
Amendment Number
Pivotal to Total Mistakes by Amendment Under Perfect Information Sincere Voting: No Feedback
0
50
100
150
1 2 3 4 5 6 7 8 9 10 11 12 13 14
Amendment Number
Pivotal to Total Mistakes by Amendment Under Perfect Information Sincere Voting: Feedback
0
50
100
150
1 2 3 4 5 6 7 8 9 10 11 12 13
Amendment Number