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.
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.
Temporary Assistance for Needy Families (TANF) leaders, policymakers, and researchers all recognize the need for TANF agencies to use the data they collect to better understand how well their programs are working and how to improve them, given the impact on the families they serve. It is often difficult, however, for agencies already stretched to capacity to prioritize and execute data use and analytics. State TANF leaders are seeking roadmaps for how to transform their organizations and become data-driven.
The Benefits Enrollment Field Guide looks at the landscape of America’s safety net benefits experience in 2023 and tracks the differences from our 2019 assessment based on expanded evaluation criteria. It also highlights successful paths to equitable, human-centered experiences. It examines online enrollment for Modified Adjusted Gross Income (MAGI) Medicaid, SNAP, TANF, the Child Care Assistance Program (CCAP), and WIC.
This report describes the human services landscape within state governments and uses case studies to show the range of approaches state governments take in structuring their human services systems. It also explores some implications of these structures for alignment and coordination within human services and with the health care sector.
This guide consolidates learning and spotlights principles, insights, and emerging practices to guide municipal leaders and public-private partnerships interested in designing basic income programs that are ethical, equitable, rigorous, informative, and consequential for local, state and national policymaking.
Chapin Hall collaborated with national policy experts, practitioners, and young adults with lived experience of homelessness to create a policy toolkit where tax, public benefits, and educational aid implications for young people participating in Direct Cash Transfer (DCT) programs are laid out in one place.
PolicyEngine is a nonprofit that provides a free, open-source web app enabling users in the US and UK to estimate taxes and benefits at the household level, while also simulating the effects of policy changes. By combining tax and benefits data, PolicyEngine helps individuals and policymakers better understand the impacts of existing policies and proposed reforms, using microsimulation models built from legislation and enhanced survey data.
