The COVID-19 pandemic has led to an explosion of research using private-sector datasets to measure business dynamics and employment in real-time. Yet questions remain about the representativeness of these datasets and how to distinguish business openings and closings from sample churn – i.e.,...

We match cell phone data to administrative school records and combine it with information on school learning modes to study effective in-person learning (EIPL) in the U.S. during the pandemic. We find large differences in EIPL for the 2020-21 school year. Public schools averaged less EIPL than...

According to data from the Labor Productivity and Costs (LPC) program, average hourly real compensation in the United States has grown consistently over time and become markedly more volatile since the mid-1980s. By contrast, data from the Current Employment Statistics (CES) imply that average...

We develop a new dynamic factor model that allows us to jointly characterize global macroeconomic and financial cycles and the spillovers between them. The model decomposes macroeconomic cycles into the part driven by global and country-specific macro factors and the part driven by spillovers...