Federal statistical agencies have pressing needs to innovate their practices in light of rapidly changing economic structure and how this changing structure interacts with the fundamental ways in which households and businesses produce and use information. This project will combine expertise in social science, survey research, and information science to address the scientific and practical problems that the statistical system must confront. It will advance the science of measurement and serve to renew the statistical system both by bringing frontier methodology to measurement problems faced by the statistical agencies. This study will also nurture a new generation of scholars, both within the statistical agencies and academia, who will collaboratively address these issues.
This project will utilize administrative data and data generated by households and businesses in the course of their normal activities to produce economic and demographic measurements that currently rely on surveys. This will allow researchers to develop and evaluate methodologies that use the vast constellation of data generated by ordinary activity in a modern society and that protect the privacy of individuals and businesses.
Researchers will examine administrative records created by businesses, individuals, and governments, streams of data from social media sites on the World Wide Web, and detailed geospatial data. They will analyze these multiple sources of data and relate them to data collected on surveys. It aims to improve survey measurements of economic and demographic data and potentially supplement or replace surveys with statistics based on administrative, Web-based, and geospatial data. Applications of these approaches include the following: using linked survey-administrative data to assess attrition, selective non-response, and measurement error in surveys; using Web-based social media to measure job loss, job creation, small business creation, and informal economic activity; using administrative geo-spatial data to enhance small-area estimates; and training in the use and creation of linked survey-administrative datasets.
Other collaborators from U-M include John Bound and Charles Brown from the College of Literature, Sciences, and the Arts, and Margaret Levenstein from the Ross School of Business.