Post on 11-Jan-2016
description
Visibility of Contributions and Cost of Information: An Experiment on
Public Goods
Anya C. SavikhinThe University of Chicago
Vernon Smith Experimental Economics Laboratory, Purdue University
Roman M. SheremetaChapman University
Economic Science Association World Meetings 2010
MotivationRecommendation from existing literature for increasing
contributions: recognize all contributors in easily accessible location (Andreoni and Petrie, 2004; Rege and Telle, 2004)
Too many contributors and this becomes difficult
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Visibility of InformationCharities may publicize names of largest donors – this
may also introduce some degree of competition between contributors concerned about prestigeLess costly to viewDonors who contribute small amounts are not recognized
All names could be publicized but this list is long (Yahoo)Costly to viewAll donors (even small amounts) are recognized
Contribution: Is it more effective to recognize all contributors (but this information may not be visible), or recognize only top contributors?
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Experimental DesignProcedures
– z-Tree 3.3.6 (Fischbacher, 2007) – Subjects earned $14 each on average (20 francs = $1, 2
periods selected for payment)– Session lasted for about 45-60 minutes
Public Goods Game (VCM) (Groves and Ledyard, 1977)– Fixed matching into groups of 5 participants , same groups for
entire session (20 periods)– Endowment of 80 experimental francs per period– MPCR = 0.4– End of each round: ranked members and display contribution
of each member
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Experimental Treatments(N)
Control (none shown)
(T) Only top 2 recognized
(A) All contributors
recognized
(AC) All recognized, costly to view
(3 francs)
40 (2 sessions) 40 (2 sessions) 40 (2 sessions) 40 (2 sessions)
Digital photos with name to identify subjects to one another (similar to Andreoni and Petrie, 2004)
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Results: OverviewResult 1: A significantly
increases contributions relative to N
Result 2: T increases contributions only marginally relative to N
Result 3: AC does not have a significant effect on contributions as compared to A with 20 periods and 40 individuals in the AC treatment, the number of times photos are viewed is 74/800 (9.2%).
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Leaders, Laggards, Prestige, Guilt
• “Leaders” set an example by contributing a lot– Any individual who contributed 75%+ of endowment in the 1st period
• “Laggards” contribute little– Any individual who contributed 25%- of endowment in the 1st period
• Prestige effect: Causes to contribute large amounts of endowment if I am recognized – more “leaders”
• Guilt effect: Causes to contribute if my small amount is recognized – fewer “laggards”
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Prestige and Guilt
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(N) (T) (A) (AC)
Compare to the Baseline (N)
☝☝Leaders
(Laggards are not explicitly revealed)
☝☝Leaders
☟☟Laggards
☝Leaders
☟Laggards
✔
Result 4: T not statistically significantly different in leaders or laggards relative to N
Result 5: A increases leaders & decreases laggards relative to N.
Result 6: AC similar in leaders as A, but significantly more laggards than A
✔ ✔
✔
☝
✘
Overall Distribution of Contributions
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“Followers”• The “social interaction effect” increases contributions
of followers given more leaders, and decreases contributions of followers given more laggards
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Conclusions• Replicates previous findings that revealing identities
significantly increases overall contributions
• We find that display of all information, even if it is costly to view, is more effective than displaying only top contributors– By increasing proportion of leaders and decreasing proportion of
laggards– This causes contributions by followers to increase
• Designers of online community groups and charities should display full information, even if it is costly to view
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