Using Linked Administrative Data to Measure Earnings Mobility of Public Assistance Recipients during the Great Recession

• Main Authors: Sally Wallace, David Sjoquist, Brett Mullins
• Format: Article
• Language: English
• Published: Swansea University 2019-11-01
• Series: International Journal of Population Data Science
• Online Access: https://ijpds.org/article/view/1184

There is a great deal of interest and concern in the trends in income inequality in the United States and how it inequality has changed since the Great Recession. Various reasons for this divide have been offered but are notoriously difficult to evaluate due to data constraints. Public sector programs aimed at alleviating poverty are also difficult to measure because of data issues. In this paper, we estimate the impact of one of the largest federal support programs in the U.S. on income mobility of at risk populations. The Supplemental Nutrition Assistance Program (SNAP) serves low income families by providing significant food benefits. In this paper, we create a dataset linking SNAP (food stamp) administrative records (over 1 million records per year) to Department of Labor earnings records (over 4 million records per year) at the individual level from 2001-2016. Using these uniquely matched administrative records, we can track earnings mobility over time as one measure of the effectiveness of a public assistance program at a point in time (which will inform policy decisions with respect to temporary measures, especially in recessions). We provide results for several time periods, but hone in on the pre-and post Great Recession period as a means to understand the impact of deep economic change on income mobility. As mobility itself is multifaceted concept, we capture a variety of measures/indices and highlight the usefulness and limitations of administrative data for the analysis. Tracking several mobility indices over time with varying time windows we can identify empirical benchmarks applied to administrative to measure the future impacts as well and to tailor government support programs.