The first paper examines TANF sanctions and employment outcomes across the county-level welfare-to-work (WTW) systems in California during the COVID-19 pandemic, using a racial equity lens. The study finds that racial disparities in sanction and exit-with-earnings rates, which vary across the stages of the pandemic. These findings offer insight into the operation of racial disparities through WTW systems and question how effectively the program supports its primary clients, predominantly low-income families and single mothers of color. The second paper also focuses on the COVID-19 pandemic era, in comparison to the Great Recession, examining the extent to which the safety net mitigated earnings losses among single mothers. The authors find that rapid, substantial expansions in the safety net--especially food assistance and tax benefits--during the pandemic recession buffered single-mother families from economic hardship to a greater extent than in the Great Recession.
The third and fourth papers explore local and state policy innovations that support working families with young children. The third paper finds that New York City's Universal Pre-K program increases maternal labor force participation and families' economic well-being. The fourth paper examines the long-term effects of California's Paid Family Leave program on mothers' employment. It finds that significant and positive employment effects are only present in the first year after childbirth, while these effects fade over time.
Altogether, this panel takes a broad look at how social welfare policies shape low-income families' work and economic well-being. Researchers analyze work as one part of economic well-being alongside equality, benefit generosity and availability, and access to income and essential resources. We take a comprehensive approach to assessing the safety net, including programs implemented by cities, states, and federal governments. Together, these papers illustrate how social policy is a flexible tool that can support families' well-being.