This study investigates how administrative burdens influence differential receipt of income transfers after a family member loses a job, looking at Unemployment Insurance, Temporary Assistance for Needy Families, and the Supplemental Nutrition Assistance Program.
This analysis explores the potential reduction in poverty rates across all U.S. states if every eligible individual received full benefits from seven key safety net programs, highlighting significant decreases in overall and child poverty.
The Temporary Assistance for Needy Families (TANF) Data Collaborative Pilot Initiative is a component of the TANF Data Innovation project. The 30-month pilot offered technical assistance and training to support cross-disciplinary teams of staff at eight state and county TANF programs in the routine use of TANF and other administrative data to inform policy and practice.
A modernized public benefits system would better serve program participants, administrators, policy makers, and taxpayers. This paper proposes a set of principles both define the desired future state and outline the values that shape decision making along the way. Practices describe the processes needed to achieve modernization.
Oklahoma Human Services (OKDHS) modernized their service delivery by reducing their real estate footprint, designing trauma-informed and user-friendly spaces, and expanding an embedded worker program to improve accessibility and client experience. Through their "Service First" strategy, OKDHS aims to create more equitable and compassionate interactions, reaching vulnerable populations while addressing high occupancy costs.
This GitHub repository includes resources that users of the UI wage data toolkit may find helpful. It covers a variety of topics, including equity, data security, programming, and data QC tips. It also serves as a place for our team to continue to post information that the TANF Data Collaborative (TDC) pilot sites found useful during our partnerships with them.
This nine-minute video, produced after the completion of the TANF Data Collaborative (TDC) Pilot, features staff members from the California, Colorado, Minnesota, and Virginia TANF agencies reflecting on their challenges, accomplishments, and general experiences during the pilot. In particular, they describe their research questions and discuss building data capacity, integrating datasets, networking with other states, increasing collaboration between state and county agencies, learning new technical skills, and the benefits of being able to draw from diverse skillsets, all within the context of the TDC Pilot.
This toolkit is designed to assist state and local TANF agencies in accessing, linking, and analyzing employment data from unemployment insurance (UI) systems. The toolkit provides practical guidance on using UI wage data for program monitoring, reporting, and evaluation, and it may be valuable for other human services agencies and policymakers interested in improving workforce outcomes. The report highlights four key sections, covering the purpose of the toolkit, challenges in accessing UI wage data, methods for linking data sources, and instructions for preparing data for analysis. Additionally, an accompanying GitHub repository offers open-source code and resources for data processing and analysis. This toolkit serves as a starting point for TANF leaders who want to access and analyze UI wage data and offers the essential building blocks you will need to get started on your data analysis journey.
On May 19, 2023, the Digital Benefits Network published a new, open dataset documenting authentication and identity proofing requirements across online SNAP, WIC, TANF, Medicaid, child care (CCAP) applications, and unemployment insurance applications.
Policymakers, program administrators, federal leaders, researchers, and advocates are increasingly focused on using administrative data to build evidence for improving government programs. Achieving this goal requires accessible data sources and the capacity to use them, yet stakeholders have little information about the baseline level of state capacity in these areas. How does one measure concepts such as “effective data use” and “analytic capacity?” This brief reports findings from a pioneering and comprehensive needs assessment that examined the capacity of Temporary Assistance for Needy Families (TANF) programs in 54 U.S. states and territories to analyze data used for program improvement, monitoring, and evidence-building. The needs assessment provides a foundation for technical assistance and continued improvement for the TANF program and may also provide valuable insights and frameworks for other state-administered human services programs.
Government agencies at all levels collect administrative data in the course of their day-to-day operations. While such information has been used to determine effectiveness through program evaluations for many years, program administrators view it increasingly as a valuable resource that can also be used to improve program performance. For example, administrative data from employment and public benefits programs such as Temporary Assistance for Needy Families (TANF) can offer insights into families’ unmet needs and ways to improve services.
