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Visibility of Contributions and Cost of Information: An Experiment on Public Goods

Economic Science Association World Meetings 2010. Visibility of Contributions and Cost of Information: An Experiment on Public Goods. Roman M. Sheremeta Chapman University. Anya C. Savikhin The University of Chicago Vernon Smith Experimental Economics Laboratory, Purdue University.

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Visibility of Contributions and Cost of Information: An Experiment on Public Goods

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  1. Economic Science Association World Meetings 2010 Visibility of Contributions and Cost of Information: An Experiment on Public Goods Roman M. Sheremeta Chapman University Anya C. Savikhin The University of Chicago Vernon Smith Experimental Economics Laboratory, Purdue University

  2. Motivation • Recommendation 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

  3. Visibility of Information • Charities may publicize names of largest donors – this may also introduce some degree of competition between contributors concerned about prestige • Less costly to view • Donors who contribute small amounts are not recognized • All names could be publicized but this list is long (Yahoo) • Costly to view • All 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?

  4. Experimental Design • Procedures • 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

  5. Digital photos with name to identify subjects to one another (similar to Andreoni and Petrie, 2004)

  6. Results: Overview • Result 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%).

  7. 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” 7

  8. Prestige and Guilt ✔ ✘ ✔☝ ✔ ✔ • 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 8

  9. Overall Distribution of Contributions 9

  10. “Followers” • The “social interaction effect” increases contributions of followers given more leaders, and decreases contributions of followers given more laggards

  11. 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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