Studies of experimental and betting markets have shown that markets are able to efficiently aggregate information dispersed over many traders. We study information aggregation in Arrow–Debreu markets using a novel information structure. Compared to previous studies, the information structure is more complex, allows for heterogeneity in information among traders—which provides insights into the way in which information is gradually disseminated in the market—and generates situations in which all traders hold identical beliefs over the traded assets’ values, thus providing a harsh stress test for belief updating. We find little evidence for information aggregation and dissemination in early rounds. Nonetheless, after traders gain experience with the market mechanism and structure, prices converge to reveal the true state of the world. Elicited post-market beliefs reveal that markets are able to efficiently aggregate dispersed information even if individual traders remain uninformed, consistent with the marginal trader hypothesis.

When the information of many individuals is pooled, the resulting aggregate often is a good predictor of unknown quantities or facts. This aggregate predictor frequently outperforms the forecasts of experts or even the best individual forecast included in the aggregation process (“wisdom of crowds”). However, an appropriate aggregation mechanism is considered crucial to reaping the benefits of a “wise crowd”. Of the many possible ways to aggregate individual forecasts, we compare (uncensored and censored) arithmetic and geometric mean and median, continuous double auction market prices and sealed bid-offer call market prices in a controlled experiment. We use an asymmetric information structure, where participants know different sub-sets of the total information needed to exactly calculate the asset value to be estimated. We find that prices from continuous double auction markets clearly outperform all alternative approaches for aggregating dispersed information and that information lets only the best-informed participants generate excess returns.

Monetary incentives are a procedural pillar in experimental economics. By applying four distinct monetary incentive schemes in three experimental finance applications, we investigate the impact of an incentive scheme’s salience on results and elicit subjects’ perception of the experienced scheme. We find (1) no differences in results between salient schemes but a significant impact if the incentive scheme is non-salient. (2) The number of previous participations has a significant impact on the perception of the incentive scheme by subjects: it strongly correlates with subjects’ motives for participation, positively contributes to subjects’ understanding of the incentive scheme, but has no influence on subjects’ motivation within the experiment. (3) Subjects favor more salient over less- or non-salient schemes in the gain domain and negatively evaluate high salience in the loss domain.

This paper presents experimental evidence about how effectively individuals learn from information coming from heterogeneous sources. In the experiment, Thai subjects observed information that came from Americans and from other Thais that they could use to help them answer a series of questions. Despite listening too little to either group, subjects demonstrated a significant amount of statistical sophistication in how they weighed observed American information relative to observed Thai information. The data indicate that subjects understood that outside information has extra value because people from the same group tend to make the same kinds of mistakes. The results illustrate the importance of forming diverse groups to solve problems.

We derive an analytic model of the inter-judge correlation as a function of five underlying parameters. Inter-cue correlation and the number of cues capture our assumptions about the environment, while differentiations between cues, the weights attached to the cues, and (un)reliability describe assumptions about the judges. We study the relative importance of, and interrelations between these five factors with respect to inter-judge correlation. Results highlight the centrality of the inter-cue correlation. We test the model’s predictions with empirical data and illustrate its relevance. For example, we show that, typically, additional judges increase efficacy at a greater rate than additional cues.