This study analyzes information production and trading behavior of banks with lending relationships. We combine trade-by-trade supervisory data and credit-registry data to examine banks' proprietary trading in borrower stocks around a large number of corporate events. We find that relationship...

Frequent, yet uninformed, fund flows in Chilean pension plans generate substantial trading in currency markets due to the high allocation to international securities. These non-fundamental flows have a significant impact on the Chilean peso, which is estimated to have a relatively low price...

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...

Economics has long studied how consumers respond to the disclosure of information about firms. We study a case in which the disclosed information is unrelated to the product or firm leadership, but which could still potentially affect consumer patronage through the mechanism of repugnance, as...

For decades credit rating agencies were viewed as trusted arbiters of creditworthiness and their ratings as important tools for managing risk. The common narrative is that the value of ratings was compromised by the evolution of the industry to a form where issuers pay for ratings. In this paper...

We propose a general equilibrium model where two special interest groups (SIGs) compete to influence public opinion. Citizens with heterogeneous priors over a binary state of the world receive reports drawn from a continuous message space by a variety of sources. The two opposite SIGs attempt to...

What do machines learn, and why? To answer these questions we import models of human cognition into machine learning. We propose two ways of modeling machine learners based on this join: feasibility-based and cost-based machine learning. We evaluate and estimate our models using a deep learning...

Quantification of operational risk has received increased attention with the inclusion of an explicit capital charge for operational risk under the new Basle proposal. The proposal provides significant flexibility for banks to use internal models to estimate their operational risk, and the...

This paper explores how non-U.S. central banks behave when firms in their economies engage in currency mismatch, borrowing more heavily in dollars than justified by their operating exposures. We begin by documenting that, in a panel of 53 countries, central bank holdings of dollar reserves are...

Global and local methods used to study open-economy incomplete-markets models yield different cyclical moments, impulse responses, spectral densities and precautionary savings. Endowment and RBC model solutions obtained with first-order, higher-order, and risky-steady-state local methods are...