State-level data on TANF policy changes during the COVID-19 pandemic

• Type of Material: Article
• Authors: Melvin Livingston III, Emory University; Emily C Dore, Emory University; Paul R Shafer, Boston University; Melvin D Livingston, Emory University
• Language: English
• Date: 2023-12-01
• Publisher: BioMed Central Ltd
• Publication Version: Final Published Version
• Copyright Statement: © The Author(s) 2023
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1186/s13104-023-06351-w
• Title of Journal or Parent Work: BMC Research Notes
• Volume: 16
• Issue: 1
• Start Page: 97
• End Page: 97
• Grant/Funding Information: This study was partially supported by funds from the National Center for Injury Prevention and Control (Grant No: R01CE003104) and the National Institute on Minority Health and Health Disparities (Grant No: F31MD017935). The viewpoints represented in this article are those of the authors and do not represent those of the funding agency.
• Keywords: Policy; Temporary Assistance for Needy Families; Social Welfare; Pandemics; Work requirements; United States; Welfare; Sanctions; TANF; Time limits; Poverty; Cash benefits; Humans; COVID-19
• Research Categories: Sociology, General; Health Sciences, Public Health

Abstract

Objective: COVID-19 mitigation measures prompted many states to revise the administration of their welfare programs. States adopted policies that varied across the U.S. to respond to the difficulties in fulfilling program requirements, as well as increased financial need. This dataset captures the changes made to Temporary Assistance for Needy Families (TANF) programs during the COVID-19 pandemic, from March 2020 through December 2020. The authors created this dataset as part of a larger study that examined the health effects of TANF policy changes during the COVID-19 pandemic. Data description: TANF is the main cash assistance program for low-income families in the U.S., but benefits are often conditional on work requirements and can be revoked if an individual is deemed noncompliant. Structural factors during the COVID-19 pandemic made meeting these criteria more difficult, so some states relaxed their rules and increased their benefits. This dataset captures 24 types of policies that state TANF programs enacted, which of the states enacted each of them, when the policies went into effect, and when applicable, when the policies ended. These data can be used to study the effects of TANF policy changes on various health and programmatic outcomes.