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Home | Events Archive | Incentive and Aggregation Mechanisms for Crowdsourcing

Incentive and Aggregation Mechanisms for Crowdsourcing

  • Series
  • Speaker(s)
    Benjamin Tereick, Erasmus University Rotterdam
  • Field
    Behavioral Economics
  • Location
    Erasmus University, Theil-Building, Room C1-6
  • Date and time

    November 26, 2019
    13:00 - 14:00


I give an overview over different projects from my PhD research. In my job market paper, I investigate empirically and theoretically how to make use of "meta-beliefs” to improve the information aggregation capacity of crowds. I propose a new aggregation scheme, “self-aggregation” (SELF) and show that in a model in which individuals update their beliefs in a Bayesian fashion, SELF is predicted to outperform alternatives. In an experimental test of the model, respondents solve a binary decision problem in a stylized urn experiment, in which responses and aggregation results can be directly compared to the Bayesian prescription. I find that the use of meta-beliefs improves the accuracy of the crowds’ decisions, even though individual answers differ systematically from the Bayesian prescription.

I embed this project in the general aim of my dissertation to facilitate the use of external crowds to improve decision-making. In particular, I discuss an incentive scheme to encourage truthful participation by the crowd members.