This paper studies how firm failures and the resulting disruptions to supply chains can amplify negative shocks. We develop a non-competitive model where customized supplier-customer relations increase productivity, and the relationship-specific surplus generated between firms and their...

We study the aggregate effects of supply-chain disruptions in the post-pandemic period in a heterogeneous-firm, general equilibrium model with input-output linkages and a rich set of supply chain frictions: uncertain shipping delays, fixed order costs, and storage costs. Firms optimally hold...

We explore the links between social capital and labor market networks at the neighborhood level. We harness rich data taken from multiple sources, including matched employer-employee data with which we measure the strength of labor market networks, data on behavior such as voting patterns that...

A person’s schooling years are a formative time for cognitive development, and also a period of intense social interaction and friendship formation. In this paper, we estimate the production of social capital during adolescence and its effect on wages. We develop a model where homophily and...

This paper uses data from global and Canadian surveys data to estimate the powerful linkages between social connections, their related social identities, and subjective well-being. Our explanatory variables include several measures of the extent and frequency of use of social networks, combined...

Recently collected data show that, within any manufacturing industry, vertically integrated firms tend to have larger, higher productivity plants, account for the bulk of sales, and also sell externally most of the inputs they produce. In a weak contracting environment characteristic of...

Recent supply disruptions catapulted the issue of risk in global supply chains (GSCs) to the top of policy agendas and created the impression that shortages would have been less severe if GSCs were either shorter and more domestic, or more diversified. But is this right? We start our answer by...

Since social distancing is the primary strategy for slowing the spread of many diseases, understanding why U.S. counties respond differently to COVID-19 is critical for designing effective public policies. Using daily data from about 45 million mobile phones to measure social distancing we...

We use aggregated data from Facebook to show that COVID-19 was more likely to spread between regions with stronger social network connections. Areas with more social ties to two early COVID-19 “hotspots” (Westchester County, NY, in the U.S. and Lodi province in Italy) generally had more...