We consider two ways to aggregate expert opinions using simple averages: averaging probabilities and averaging quantiles. We examine analytical properties of these forecasts and compare their ability to harness the wisdom of the crowd. In terms of location, the two average forecasts have the...

Probability forecasters who are rewarded via a proper scoring rule may care not only about the score, but also about their performance relative to other forecasters. We model this type of preference and show that a competitive forecaster who wants to do better than another forecaster typically...

Stochastic dominance permits a partial ordering of alternatives (probability distributions on consequences) based only on partial information about a decision maker's utility function. Univariate stochastic dominance has been widely studied and applied, with general agreement on classes of...

Almost stochastic dominance allows small violations of stochastic dominance rules to avoid situations where most decision makers prefer one alternative to another but stochastic dominance cannot rank them. While the idea behind almost stochastic dominance is quite promising, it has not caught on...

Consider a choice between two random variables, for which only means and variances are known. Is it possible to rank them by putting some constraints on risk preferences? We provide such a ranking by bounding how much marginal utility can change. Such bounds enable us to rank all distributions...

We investigate the cost of the opportunity delayed by working on one project with uncertain success rather than searching for a new project. We answer the question: how long should a firm work on a research project with uncertain success before abandoning it if the only alternative is to search...

When combining forecasts, a simple average of the forecasts performs well, often better than more sophisticated methods. In a prescriptive spirit, we consider some other parsimonious, easy-to-use heuristics for combining interval forecasts and compare their performance with the benchmark...

Probabilistic forecasts are necessary for robust decisions in the face of uncertainty. The M5 Uncertainty competition required participating teams to forecast nine quantiles for unit sales of various products at various aggregation levels and for different time horizons. This paper evaluates the...

This paper suggests a new normative approach for combining beliefs. We call it the evidence-first method. Instead of aggregating credences alone, as the prevailing approaches, we focus instead on eliciting a group's full probability distribution on the basis of the evidence available to its...

Important business, public policy, and personal decisions typically involve multiple objectives, which in turn can be represented by multiple attributes, and uncertainty. Assessing both multiattribute utility and multivariate distributions for the attributes can be challenging. Moreover, big...