Capitalizing on the (False) Consensus Effect: Two Tractable Methods to Elicit Private Information [Dataset]

We propose and experimentally test two tractable methods to incentivize the elicitation of private information: Benchmark and Coordination. Both mechanisms capitalize on the false consensus effect, a well-documented phenomenon that follows Bayesian reasoning. That is, individuals use their own type when predicting the type of others. Since it is not feasible to incentivize the elicitation of private information using facts, when these are not verifiable, we incentivize the respondent to reveal her perceptions about others and use that statement to predict the subject´s private information. The stronger the relationship between a subject´s type and her perception about the type of others, the more effective the mechanisms are in revealing the subject´s privately held information. In an experiment, we apply the mechanisms to reveal beliefs about probabilities. On the aggregate level, both mechanisms accurately reveal mean first-order beliefs of the population. On the subject level, the modal difference between probabilities elicited in either mechanism and actual first-order beliefs is zero. The results indicate that subjects strongly anchor their statements in Benchmark and Coordination on their private information.