Case Study
Policy Analysis

TANF Data Collaborative Pilot: Family Characteristics in Utah

TANF Data Collaborative Pilot: Family Characteristics in Utah
TANF Data Collaborative Pilot: Family Characteristics in Utah
Project Partners
MDRC, Chapin Hall at the University of Chicago, Actionable Intelligence for Social Policy, Coleridge Initiative
Sector of partners
Benefits Program
TANF: Temporary Assistance for Needy Families
Level of government

Problem Statement

The project explores characteristics of families who exit and return to Utah's TANF cash assistance program. It seeks to understand the reasons for their return and identify services that could reduce their future reliance on assistance. Data quality is also examined for its impact on understanding factors influencing benefit return.

Project Description

The project focused on analyzing data from Utah's TANF program, including eligibility data and case management records. The pilot team utilized various software tools such as SQL, Excel, and R for data extraction, descriptive analysis, and regression analysis. Cohorts of families who exited the TANF program from 2011 onwards were examined, and their outcomes were tracked for several years to understand the factors influencing their return to TANF. Five-year outcomes were assessed for the 2011 and 2014 cohorts, while a three-year analysis was conducted for the 2018 cohort, which allowed for insights into the potential impact of the COVID-19 pandemic. The analyses included descriptive statistics on demographics, household composition, and the educational level of the head of household at the time of exiting TANF. Additionally, the project investigated missing data in the educational attainment variable and its correlation with the race or ethnicity of the family's head of household.

Project Outcomes and Impact

The Utah pilot project improved data completeness on TANF participants' educational attainment. Initial findings showed racial disparities in missing education data. Education level did not strongly influence return rates to TANF. Future analyses will explore post-exit earnings, employers, industries, and the impact of education level on TANF return.

Replicable Takeaways

This project serves as a replicable model for staff from other agencies looking for examples of efforts that support the use of administrative data for learning and improvement. Policymakers, researchers, and organizations seeking to expand the use of data in state TANF agencies may find interest in this project.

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