What are the characteristics of workers in jobs likely to be initially affected by broad social distancing and later by narrower policy tailored to jobs with low risk of disease transmission? We use O NET to construct a measure of the likelihood that jobs can be conducted from home (a variant of...

This paper models a frictional labor market where employers endogenously discriminate against the long term unemployed. The estimated model replicates recent experimental evidence which documents that interview invitations for observationally equivalent workers fall sharply as unemployment...

We investigate the role of information frictions in the US labor market using a new nationally representative panel dataset on individuals' labor market expectations and realizations. We find that expectations about future job offers are, on average, highly predictive of actual outcomes. Despite...

We present new calculations of cumulative marginal tax rates (MTRs) facing low income families participating in multiple welfare programs over the period 1997-2007, the period after 1996 welfare reform but before the program expansions of the Great Recession. Our calculations are for...

We study how COVID-19 affected the prevalence, expectations, and attitudes toward remote work using specially designed surveys. The incidence of remote work remains higher than pre-pandemic levels and both men and women expect this to persist post-pandemic. Workers also report increased...

At the onset of the COVID pandemic, the U.S. economy suddenly and swiftly lost 20 million jobs. Over the next two years, the economy has been on the recovery path. We assess the labor market two years into the COVID crisis. We show that early employment dynamics were almost entirely driven by...

We report on the state of the labor market midway through the COVID recession, focusing particularly on measuring market tightness. As we show using a simple model, tightness is crucial for understanding the relative importance of labor supply or demand side factors in job creation. In tight...

We develop and calibrate a search-theoretic model of the labor market in order to forecast the evolution of the aggregate US labor market during and after the coronavirus pandemic. The model is designed to capture the heterogeneity of the transitions of individual workers across states of...

We use job vacancy data collected in real time by Burning Glass Technologies, as well as unemployment insurance (UI) initial claims and the more traditional Bureau of Labor Statistics (BLS) employment data to study the impact of COVID-19 on the labor market. Our job vacancy data allow us to...