Job Accessibility and Spatial Mismatch with Longitudinal Employment Data

The paper examines spatial mismatch using confidential longitudinal employment data. Its purpose is to increase our understanding of the implications of spatial barriers to access to low-wage work in U.S. metropolitan areas. A central assumption of the spatial mismatch literature is that accessibility to jobs is crucial for obtaining employment. The present analysis examines the importance and nature of this relationship using confidential Census longitudinal employee-employer linked microdata. In doing so, it addresses self-selection, uses a series of dependent variables based on longitudinal data, and proceeds at a detailed spatial level. In particular, it examines the opportunities available to displaced workers in terms of the spatial distribution of potentially-available jobs by industry and earnings. This research is made possible by the availability of a new confidential Census data source: the Longitudinal Employer-Household Dynamics (LEHD) data. These data provide, for over 120 million U.S. workers, confidential detailed information on job location and residential location. They are longitudinal, permitting estimation of models explaining rehiring after a separation. Likewise, measures of job accessibility are defined not only on the spatial distribution of employment but also based on the spatial distribution of new hires. Models are estimated for five Great Lakes metropolitan areas. These areas vary in size, changes in manufacturing employment, and opportunities in alternate industry sectors