Sequential Fundraising and Social Insurance

Amir Ban, Moran Koren

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations


Seed fundraising for ventures often takes place by sequentially approaching potential contributors, whose decisions are observed by other contributors. The fundraising succeeds when a target number of investments is reached. When a single investment suffices, this setting resembles the classic information cascades model. However, when more than one investment is needed, the solution is radically different and exhibits surprising complexities. We analyze a setting where contributors' levels of information are i.i.d. draws from a known distribution, and find strategies in equilibrium for all. We show that participants rely on social insurance,i.e., invest despite having unfavorable private information, relying on future player strategies to protect them from loss. Delegationis an extreme form of social insurance where a contributor will unconditionally invest, effectively delegating the decision to future players. In typical fundraising, early contributors will invest unconditionally, stopping when the target is "close enough", thus de factodelegating the business of determining fundraising success or failure to the last contributors.

Original languageEnglish
Title of host publicationEC 2020 - Proceedings of the 21st ACM Conference on Economics and Computation
PublisherAssociation for Computing Machinery
Number of pages2
ISBN (Electronic)9781450379755
StatePublished - 13 Jul 2020
Externally publishedYes
Event21st ACM Conference on Economics and Computation, EC 2020 - Virtual, Online, Hungary
Duration: 13 Jul 202017 Jul 2020

Publication series

NameEC 2020 - Proceedings of the 21st ACM Conference on Economics and Computation


Conference21st ACM Conference on Economics and Computation, EC 2020
CityVirtual, Online


  • fundraising
  • social learning

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Economics and Econometrics
  • Statistics and Probability
  • Computational Mathematics


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