Expanding TANF Program Insights

A Toolkit for State and Local Agencies on How to Access, Link, and Analyze Unemployment Insurance Wage Data

By Edith Yang, Sharon Zanti, T.C. Burnett, Richard Hendra, Dennis Culhane, Zarni Htet, Della Jenkins, Camille Préel-Dumas, Electra Small


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.

This toolkit was created to help TANF professionals develop more robust, data-driven practices using administrative data on earnings. Whether you are a frontline case worker, a data analyst, or an administrator, the toolkit is designed to help you explore strategies to access and use earnings data for program improvement purposes.


The primary purpose of this toolkit is to offer practical guidance to state and local TANF agencies on how to access, link, and analyze employment data from unemployment insurance (UI) systems for program monitoring, reporting, and evaluation. The toolkit may also be useful to other state human services agencies (for example, SNAP and Child Support) that want to expand their data use, as well as policymakers interested in supporting improved workforce outcomes. State Department of Labor agencies may also gain useful insights from the data preparation section in Part 4, as well as from the broader discussion of ways to use employment data to improve human services programs.

Further guidance on TANF data use topics can be found in the toolkit’s companion GitHub repository, which offers open source code and documentation for program administrators and researchers who are preparing employment data for analysis.

Key Findings and Highlights

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. 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.

This toolkit is meant to be a starting point for TANF leaders who want to access and analyze UI wage data. It offers the essential building blocks you will need to get started on your data analysis journey. Supplemental materials in the toolkit’s appendix, annotated bibliography, and GitHub resources folder can help you further.

Yang, Edith, Sharon Zanti, T.C. Burnett, Richard Hendra, Dennis Culhane, Zarni Htet, Della Jenkins, Camille Préel-Dumas, and Electra Small. 2022. Expanding TANF Program Insights. New York: MDRC.