Cooperation among strangers with limited information about reputation
Open accessAbstract
The amount of institutional intervention necessary to secure efficiency-enhancing cooperation in markets and organizations, in circumstances where interactions take place among essentially strangers, depends critically on the amount of information informal reputation mechanisms need transmit. Models based on full backward induction find that the necessary information is very large and recursive in nature, implausibly so outside of circumstances where there is a formal institution to process it. Models that relax backward induction find that the information demands may be quite modest. The experiment we present indicates that subjects condition their cooperation on information about their partners' immediate past action, while additional, recursive information about the partners' previous partners' reputation triggers and additional conditional response. Taken together, our results suggest that reputation is a more robust enforcement mechanism for cooperation than standard models suggest; informal stictures that punish cheaters and those who fail to punish cheaters is sufficient to generate substantial cooperation even when the benefits from cooperation are relatively modest.
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After a couple of rounds the personal experience obtained with the given co-player becomes more decisive.
“After a couple of rounds the personal experience obtained with the given co-player becomes more decisive 62 .”
From Evolution of indirect reciprocity (2005) · cites this paper as [62]
The Design of the experiment section (page unavailable) says that no two subjects were paired more than once and that subjects knew this. Its design therefore rules out gaining experience with a given co-player over several rounds; the paper instead studies decisions based on information about a new partner’s past actions. (LLM, conf=0.89)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredIn another experiment, those who give often end up with the highest payoff, so that there is a strategic advantage to generosity.
“In another experiment 62 , however, those who give often end up with the highest payoff, so that there is a strategic advantage to generosity.”
From Evolution of indirect reciprocity (2005) · cites this paper as [62]
The Conclusions (section 6; page not provided) report the opposite individual-level pattern: in every treatment, giving more gifts was negatively correlated with total payoff. Although giving raised the chance of receiving a gift, the paper says an additional gift cost the giver about 9 cents on average, rather than conferring the claimed payoff advantage. (LLM, conf=0.90)
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- Authors
- Bolton, G. E., Katok, E., & Ockenfels, A.
- Affiliations
- Pennsylvania State University (US)
- University of Cologne (DE)
- Corresponding author
- Bolton, Gary E.
- Venue
- Journal of Public Economics
- Publisher
- Elsevier BV
- Published
- 2005-08
- Volume
- 89
- Issue
- 8
- Pages
- 1457-1468
- ISSN
- 0047-2727 (ISSN-L)
- OpenAlex
- W3125077241
- Cited by
- 305
- References
- 43
- Citations by year
- 2026: 6 · 2025: 12 · 2024: 16 · 2023: 16 · 2022: 5 · 2021: 20 · 2020: 20 · 2019: 12 · 2018: 12 · 2017: 13 · 2016: 16 · 2015: 24 · 2014: 12 · 2013: 14 · 2012: 16
- FWCI
- 29.23
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Public Economics (publishedVersion, cc-by-nc-nd)
- SSRN Electronic Journal (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Science Foundation
- Deutsche Forschungsgemeinschaft
- Universität Bielefeld
- Topics
- Social Sciences › Safety Research › Experimental Behavioral Economics Studies
- Social Sciences › Decision Sciences › Management Science and Operations Research › Game Theory and Applications
- Social Sciences › Sociology and Political Science › Evolutionary Game Theory and Cooperation
- Keywords
- reputation, cost of cooperation, subgame perfect equilibrium, institutional intervention, repeated games
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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