fbpx Using prediction markets to predict the outcomes in the Defense Advanced Research Projects Agency’s next-generation social science programme - Yiling Chen | Harvard Kennedy School

Additional Authors:

  • Yiling Chen

Abstract

June 24, 2021, Paper: "There is evidence that prediction markets are useful tools to aggregate information on researchers’ beliefs about scientific results including the outcome of replications. In this study, we use prediction markets to forecast the results of novel experimental designs that test established theories. We set up prediction markets for hypotheses tested in the Defense Advanced Research Projects Agency’s (DARPA) Next Generation Social Science (NGS2) programme. Researchers were invited to bet on whether 22 hypotheses would be supported or not. We define support as a test result in the same direction as hypothesized, with a Bayes factor of at least 10 (i.e. a likelihood of the observed data being consistent with the tested hypothesis that is at least 10 times greater compared with the null hypothesis). In addition to betting on this binary outcome, we asked participants to be.."

Non-HKS Author Website - Yiling Chen