Panel Paper: Local Economic Conditions and SNAP Caseloads

Thursday, November 8, 2012 : 10:55 AM
International E (Sheraton Baltimore City Center Hotel)

*Names in bold indicate Presenter

Katie Fitzpatrick, Seattle University, Erik Scherpf, US Department of Agriculture and Laura Tiehen, U.S. Department of Agriculture

With more than 40 million Americans currently receiving benefits, the caseload of the Supplemental Nutrition Assistance Program (SNAP), formerly the food stamp program, is at an historic high. A large literature exists on the economic and other determinants of SNAP caseloads at the state and national level, but no work has yet comprehensively examined the dynamic and spatial aspects of caseload growth at the sub-state level. We utilize a unique dataset of monthly, county-level SNAP caseloads from January 2000 through January 2010 to estimate the effect of local economic conditions on the caseload, controlling for the programmatic changes occurring in the SNAP program over this period.

This paper will shed new light on how macroeconomic changes affect the growth of the caseload. Despite the great diversity of economic conditions and SNAP caseloads within states, due to the lack of available data, previous work has not examined the determinants of SNAP caseloads at the sub-state level for the entire country. Our focus on the county-level caseloads better captures the conditions of the local economy which, as research on cash welfare has shown, is likely to be a better predictor of local caseloads than state-level measures.

In addition, the time period covered by our study captures substantial variation in macroeconomic conditions and SNAP caseloads within counties that occurred with the Great Recession. Our focus on measures of county-level unemployment rates, employment growth, employment-to-population ratios, wages, and housing prices will capture the dramatic change in local conditions to sort out which economic indicators are most important for SNAP growth.

Our results will assist policymakers in predicting how the caseload will evolve as the nation emerges from the effects of the Great Recession. In particular, the finer geographic detail will assist federal and state officials in optimally allocating administrative and social services across local areas.