Expanding TANF Program Insights: A Toolkit for State and Local Agencies on How to Access, Link, and Analyze Unemployment Insurance Wage Data

State and local leaders at Temporary Assistance for Needy Families (TANF) agencies have been increasingly focused on using administrative data from TANF and other state agencies to better assess how well programs are working, inform policies and practices, and, ultimately, improve the lives of families with low incomes. Economic mobility through employment retention and advancement is of particular interest to TANF leaders, but administrative data on TANF recipients’ earnings are often difficult to access except for the purpose of investigating noncompliance.

Since 2017, the TANF Data Innovation (TDI) project has been helping state agencies harness their administrative data to improve family outcomes. Sponsored by the Administration for Children and Families within the U.S. Department of Health and Human Services, TDI is being led by MDRC in partnership with Chapin Hall at the University of Chicago, Actionable Intelligence for Social Policy at the University of Pennsylvania, and the Coleridge Initiative. This toolkit is part of that effort.

The aim of the toolkit is to offer practical guidance to state and local TANF agencies on how to access, link to, and analyze Unemployment Insurance (UI) wage data from state Departments of Labor for program monitoring, reporting, and evaluation. As such, the toolkit consists of a guidance brief and a companion GitHub repository:

The guidance brief is organized into four main sections: (1) a short introduction that lays out the purpose of the toolkit as well as background information on UI wage data and the kinds of research questions that data can be used to answer, (2) a description of common challenges to accessing state UI wage data and strategies to address those challenges, (3) methods for linking UI wage data to other data sources, including emerging advanced methods that are more secure, and (4) instruction for preparing UI wage data for analysis, including how to create common employment-related outcomes that the field has used for decades to measure employment trends, stability, and mobility.

The GitHub repository provides open source and accessible code for use with the fourth section of the guidance brief, described above. It includes code to use to look for common UI wage data issues and guidance on how to resolve those issues. In addition, documents in the repository walk users through a strategy for processing UI wage data to create an analysis file and employment-related outcomes of interest. Finally, the repository has a resources folder with related supplemental materials that have emerged from the larger TDI project as well as from the research team’s meetings with members of an expert working group made up of researchers, policy professionals, and state and local TANF agency staff members that toolkit users may find helpful.