This paper examines circumstances under which subjectivity enhances the effectiveness of inductive reasoning. We consider agents facing a data generating process who are characterized by inference rules that may be purely objective (or data-based) or may incorporate subjective considerations....

Decision theory can be used to test the logic of decision making---one may ask whether a given set of decisions can be justified by a decision-theoretic model. Indeed, in principal-agent settings, such justifications may be required---a manager of an investment fund may be asked what beliefs she...

We present a model of inductive inference that includes, as special cases, Bayesian reasoning, case-based reasoning, and rule-based reasoning. This unified framework allows us to examine, positively or normatively, how the various modes of inductive inference can be combined and how their...

We formulate a notion of stable outcomes in matching problems with one-sided asymmetric information. The key conceptual problem is to formulate a notion of a blocking pair that takes account of the inferences that the uninformed agent might make from the hypothesis that the current allocation is...

A large literature uses matching models to analyze markets with two-sided heterogeneity, studying problems such as the matching of students to schools, residents to hospitals, husbands to wives, and workers to firms. The analysis typically assumes that the agents have complete information, and...

We examine a repeated interaction between an agent, who undertakes experiments, and a principal who provides the requisite funding for these experiments. The repeated interaction gives rise to a dynamic agency cost — the more lucrative is the agent's stream of future rents following a failure,...

“Crowds” are often regarded as “wiser” than individuals, and prediction markets are often regarded as effective methods for harnessing this wisdom. If the agents in prediction markets are Bayesians who share a common model and prior belief, then the no-trade theorem implies that we...

``Crowds'' are often regarded as ``wiser'' than individuals, and prediction markets are often regarded as effective methods for harnessing this wisdom. If the agents in prediction markets are Bayesians who share a common model and prior belief, then the no-trade theorem implies that we should...

People reason about uncertainty with deliberately incomplete models, including only the most relevant variables. How do people hampered by different, incomplete views of the world learn from each other?We introduce a model of “model-based inference.” Model-based reasoners partition an...

People reason about uncertainty with deliberately incomplete models, including only the most relevant variables. How do people hampered by different, incomplete views of the world learn from each other? We introduce a model of “model-based inference.” Model-based reasoners partition an...