Small-area estimates from consumer trace data

Abstract

BACKGROUND Timely, accurate, and precise demographic estimates at various levels of geography are crucial for planning, policymaking, and analysis. In the United States, data from the decennial census and annual American Community Survey (ACS) serve as the main sources for subnational demographic estimates. While estimates derived from these sources are widely regarded as accurate, their timeliness is limited and variability sizable for small geographic units like towns and neighborhoods. OBJECTIVE This paper investigates the potential for using nonrepresentative consumer trace data assembled by commercial vendors to produce valid and timely estimates. We focus on data purchased from Data Axle, which contains the names and addresses of over 150 million Americans annually.