“Big data” gives markets access to previously unmeasured characteristics of individual agents. Policymakers must decide whether and how to regulate the use of this data. We study how new data affects incentives for agents to exert effort in settings such as the labor market, where an agent's...

We conduct laboratory experiments on variants of market scoring rule prediction markets, under different information distribution patterns, in order to evaluate the efficiency and speed of information aggregation, as well as test recent theoretical results on manipulative behavior by traders. We...

This paper studies a robustness of solutions in finite depth of reasoning models. The level-k and cognitive hierarchy models conventionally assume that each player has a commonly known anchor behavior to obtain a sharp prediction. We provide a general framework to examine whether the obtained...

We describe a methodology for making counterfactual predictions when the information held by strategic agents is a latent parameter. The analyst observes behavior which is rationalized by a Bayesian model in which agents maximize expected utility, given partial and differential information...

We describe a methodology for making counterfactual predictions when the information held by strategic agents is a latent parameter. The analyst observes behavior which is rationalized by a Bayesian model in which agents maximize expected utility given partial and differential information about...

Self-perception and perception by others can diverge. Such differences can play an important role in corporate governance settings, for example in the context of task allocation. We run two experiments to study how predictions about own performance and the performance of others develop over time...