The returns to skills and the nature of work differ systematically across labor markets of different sizes. Prior research has pointed to worker interactions, technological innovation, and specialization as key sources of urban productivity gains, but has been limited by the available data in...

We study the evolution of US mortgage credit supply during the COVID-19 pandemic. Although the mortgage market experienced a historic boom in 2020, we show there was also a large and sustained increase in intermediation markups that limited the pass-through of low rates to borrowers. Markups...

Factor models are generally subject to a rotational indeterminacy, meaning that individual factors are only identified up to a rotation. In the presence of local factors, which only affect a subset of the outcomes, we show that the implied sparsity of the loading matrix can be used to solve this...

We present a novel approach to finite Rational Inattention (RI) models based on the ignorance equivalent, a fictitious action with state-dependent payoffs that effectively summarizes the optimal learning and conditional choices. The ignorance equivalent allows us to recast the RI problem as a...

Can social influence effects help explain regional heterogeneity in refinancing activity? Neighborhood social influence effects have been shown to affect publicly observable decisions, but their role in private decisions, like refinancing, remains unclear. Using precisely geolocated data and a...

There has been a great deal of interest recently in understanding the potential role of fintech firms in expanding credit access to the underbanked and credit-constrained consumers. We explore the supply side of fintech credit, focusing on unsecured personal loans and mortgage loans. We...

We present a general framework for Bayesian estimation and causality assessment in epidemiological models. The key to our approach is the use of sequential Monte Carlo methods to evaluate the likelihood of a generic epidemiological model. Once we have the likelihood, we specify priors and rely...

We propose methods for constructing regularized mixtures of density forecasts. We explore a variety of objectives and regularization penalties, and we use them in a substantive exploration of Eurozone inflation and real interest rate density forecasts. All individual inflation forecasters (even...

We survey Bayesian methods for estimating dynamic stochastic general equilibrium (DSGE) models in this article. We focus on New Keynesian (NK)DSGE models because of the interest shown in this class of models by economists in academic and policy-making institutions. This interest stems from the...

Using an estimated dynamic stochastic general equilibrium model, I show that shocks to a common international stochastic trend explain on average about 10% of the variability of output in several small developed economies. These shocks explain roughly twice as much of the volatility of...