C91 - Laboratory, Individual Behavior
Laboratory, Individual Behavior
We theoretically and empirically study an incomplete information model of social learning. Agents initially guess the binary state of the world after observing a private signal. In subsequent rounds, agents observe their network neighbors’ previous guesses before guessing again. Types are drawn from a mixture of learning models—Bayesian, where agents face incomplete information about others’ types, and DeGroot, where agents follow the majority of their neighbors’ previous period guesses.
The paper reports the result of an experimental game on asset integration and risk taking. We and some evidence that winnings in earlier rounds affect risk taking in subsequent rounds, but no evidence that real life wealth outside the experiment affects risk taking. Controlling for past winnings, participants receiving a low endowment in a round engage in more risk taking. We test a 'keeping-up-with-the-Joneses' hypothesis and and some evidence that subjects seek to keep up with winners, though not necessarily average earnings.