About NCRN - Michigan Node
The University of Michigan NCRN node addresses the specific analytic and operational requirements of the Census Bureau and other federal statistical agencies to improve their estimates while reducing costs and respondent burden. The project uses administrative data, and more generally, data generated by households and businesses in the course of their normal activities, to produce economic and demographic measurements that currently rely on surveys. The project develops and evaluates methods to use the vast constellation of data generated by ordinary activity in a modern society while protecting the privacy of individuals and businesses. The project analyzes administrative and transaction records created by businesses, individuals, and governments, data from social media sites, and detailed geospatial data from satellite imagery. The project 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.
Key contributions of the Michigan node include
- Using Tweets to construct real-time indicators of labor market transitions
- Using account data to study the relationship of spending and income
- Joint analysis of survey and administrative data
- Implementing new methods for measuring poverty, income, and food insecurity in large-scale surveys
- Using satellite imagery to measure changes in urbanization during the Great Recession
- Training the next generation of scholars in the use of the Census Bureau’s Survey of Income and Program Participation (SIPP)
The Federal statistical agencies have pressing needs to innovate in light of the rapidly changing structure of the economy and the interaction of these changes with the fundamental ways in which households and businesses produce and use information. This project combines expertise in social science, survey research, and information science to address the scientific and practical problems that the statistical system must confront. The project advances the science of measurement and serves to renew the statistical system both by bringing frontier methodology to measurement problems faced by the statistical agencies and by nurturing a new generation of scholars, both within the statistical agencies and academia, who will collaboratively address these issues.
This work is supported by the National Science Foundation under Grant No. SES 1131500.