When giving to one charity, individuals face two types of uncertainty, descriptive and normative. We report a between-subjects charitable-giving experiment which provides first data on normative uncertainty (n=1890). In our experiment, participants can bid for either descriptive information,...

We study the problem a diagnostic expert (e.g., a physician) faces when offering a diagnosis to a client (e.g., a patient) that may be based only on her own diagnostic ability or supplemented by a diagnostic test — conventional and artificial intelligence (AI) tools alike — revealing the...

We analyze the role of risk limits in the provision of incentives to acquire valuable information for efficient risk management. We study the optimal contract of a trader who (a) must privately exert costly effort in order to collect information and (b) may have access to a costly second opinion...

We address the problem of choosing a portfolio of policies under “deep uncertainty.” We introduce the idea of belief dominance as a way to derive a set of non-dominated portfolios and robust individual alternatives. Our approach departs from the tradition of providing a single recommended...

We propose a decomposition to distinguish between Knightian uncertainty (ambiguity) and risk, where the first measures the uncertainty about the probability distribution generating the data, while the second measures uncertainty about the odds of the outcomes when the probability distribution is...

This comment was published in the International Journal of Forecasting symposium on the Soyer-Hogarth experiment (Vol. 28, No. 3, July/Sept. 2012, pp. 712-714). The experiment evaluates the ability of expert econometricians to make predictions based on commonly provided regression output. Visual...