Requiring agents with private information to select from a menu of incentive schedules can yield efficiency gains. It will do so if, and only if, agents will receive further private information after selecting the incentive schedule but before taking the action that determines where on the...

In an earlier paper, we showed that the value of shadow prices depends on how the government contemplates re- equilibrating the economy to the perturbation associated with any project, except in the extreme case where the government has chosen all policy instruments optimally. Only under...

We propose and study properties of several estimators of variance decomposition in the local-projections framework. We find for empirically relevant sample sizes that, after being bias corrected with bootstrap, our estimators perform well in simulations. We also illustrate the workings of our...

We outline a method to provide advice on optimal monetary policy while taking policymakers' judgment into account. The method constructs Optimal Policy Projections (OPPs) by extracting the judgment terms that allow a model, such as the Federal Reserve Board's FRB/US model, to reproduce a...

This paper shows that product design shapes search frictions and that intermediaries leverage this channel to increase their rents in the context of the U.S. municipal bond market. The majority of bonds are designed via negotiations between a local government and its underwriter. They are then...

We develop and estimate a model of consumer search with spatial learning. Consumers make inferences from previously searched objects to unsearched objects that are nearby in attribute space, generating path dependence in search sequences. The estimated model rationalizes patterns in data on...

Economists have long hypothesized that large and thick labor markets facilitate the matching between workers and firms. We use administrative data from the LEHD to compare the job search outcomes of workers originally in large and small markets who lost their jobs due to a firm closure. We...