In recent years, considerable attention has been devoted to the development of statistical methods for the analysis of uncertainty in cost-effectiveness analysis, with a focus on situations in which the analyst has patient-level data on the costs and health effects of alternative interventions....

We introduce the concept of a triad census of a digraph arid show how it can be used to enumerate various types of subgraph configurations. We give the basic probabilities needed for computing means and variances for a triad census under the U-MAN distribution for digraphs. These concepts are...

This paper characterizes identification in dynamic linear models. It shows that identification restrictions are linear in the structural parameters and are therefore easy to use. Using these restrictions, it analyzes the role of exogenous variables in helping to achieve identification

A decision maker tests whether the gradient of the loss function evaluated at a judgmental decision is zero. If the test does not reject, the action is the judgmental decision. If the test rejects, the action sets the gradient equal to the boundary of the rejection region. This statistical...

We introduce a structural vector autoregressive (SVAR) model with each of the mutually independent errors following a skewed generalized t-distribution that is more flexible than a Student's t-distribution typically considered. Hence, the effect of potential distributional misspecification is...

Policy makers depend on economists, statisticians, and other social scientists to make accurate observations and draw solid conclusions from quantitative analysis. Econometrics, for example, has come a long way in the past century and guides many decisions made today. On the other hand, some...

Can a group be an orthodox rational agent? This requires the group's aggregate preferences to follow expected utility (static rationality) and to evolve by Bayesian updating (dynamic rationality). Group rationality is possible, but the only preference aggregation rules which achieve it (and are...

We introduce evolutionary dynamics for two-action games where agents with diverse preferences use statistical inference to guide their behavior. In each period, agents are randomly selected to revise actions. They draw a random sample of other agents’ actions, use statistical inference to...

Under rotation-equivariant decision theory, sample covariance matrix eigenvalues can be optimally shrunk by recombining sample eigenvectors with a (potentially nonlinear) function of the unobservable population covariance matrix. The optimal shape of this function reflects the loss/risk that is...