Cities exist because of the productivity gains that arise from clustering production and workers, a process called agglomeration. How important is agglomeration for aggregate growth? This paper constructs a dynamic stochastic general equilibrium model of cities and uses it to estimate the effect of local agglomeration on aggregate growth. We combine aggregate time-series and city-level panel data to estimate the model's parameters via generalized method of moments. The estimates imply a statistically and economically significant impact of local agglomeration on the growth rate of per capita consumption, raising it by about 10%.

We study the impact of widespread adoption of work-from-home (WFH) technology using an equilibrium model where people choose where to live, how to allocate their time between working at home and at the office, and how much space to use in production. Motivated by cross-sectional evidence on WFH, we model WFH as a complement to work at the office. Simulations of the model indicate that the pandemic induced a large change to the relative productivity of WFH that substantially increased home prices and will permanently affect incomes, income inequality, and city structure.

This article provides a comprehensive history of default risk for newly originated home mortgages in the USA over the past quarter century. The loan-level source data include the entire guarantee book for Fannie Mae and Freddie Mac. We track many loan characteristics and produce a summary measure of risk. Among our many results, we show that mortgage risk had already risen in the 1990s, planting seeds of the financial crisis well before the actual event. Our results also cast doubt on explanations of the crisis that focus on borrowers with low credit scores. The aggregate series are available for download at https://www.fhfa.gov/papers/wp1902.aspx.