New Approaches to Creating Data for Economic Geographers

Matthew Freedman, Cornell University
Julia Lane, National Science Foundation
Marc Roemer, U.S. Census Bureau

Abstract

Policymakers, faced with increasing demands to make decisions at a local level, are turning to statistical agencies to provide local data. Advances in matching technology, combined with the reduced cost of archiving, indexing, storing, and curating large-scale datasets, now mean that it is technically feasible to provide information at fine levels of geographic detail by means of combining administrative and survey datasets at lower cost and with potentially greater coverage. This article describes an approach that uses administrative data from U.S. unemployment insurance records to enhance the coverage and accuracy of work location information in the American Community Survey.