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The Great Recession and the Changing Geography of Food Stamp Receipt

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An Erratum to this article was published on 09 January 2014

Abstract

The Great Recession has been distinctive in driving up unprecedented levels of participation in the Supplemental Nutrition Assistance Program (SNAP). This study extends the literature on the geography of SNAP receipt by (1) examining change in SNAP receipt across US counties during the Great Recession and (2) identifying how changes in other local characteristics were associated with this outcome. Our analysis draws on data from the US Department of Agriculture and other secondary sources. We use descriptive statistics, mapping, and weighted least squares spatial regression models to examine county-level variation (N = 2,485) in the percentage-point change in SNAP receipt between 2007 and 2009. Our findings reveal substantial local-level variation in the change in SNAP stamp use during the downturn. We find that counties with the greatest levels of change in SNAP participation tend to be regionally clustered. Our regression analysis shows that areas where the signature characteristics of the Great Recession were most pronounced (i.e., home foreclosures and unemployment) were precisely the places where SNAP use jumped most, not places with historically high levels of SNAP participation. Overall, this study demonstrates that change in SNAP receipt was geographically uneven during the Great Recession, and that local and regional configurations matter in shaping this variation. These results hold a range of implications for public policy, including opportunities for regionally targeted outreach and investment in SNAP and the use of the program as a responsive form of local stimulus during periods of economic crisis.

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Notes

  1. A product of the 1960s War on Poverty, the program was signed into law as the Food Stamp Act of 1964. The name of the program officially changed from the Food Stamp Program to the Supplemental Nutrition Assistance Program (SNAP) in 2008.

  2. It should be noted that we are measuring changes in take-up rather than eligibility. In Fiscal Year 2010 about three-quarters of those eligible for SNAP participated in the program (Rosenbaum 2013).

  3. Specifically, the states excluded from our analysis due to a lack of available data include Connecticut, Idaho, Maine, Massachusetts, Missouri, Montana, Nebraska, New Hampshire, New York, Oregon, Rhode Island, Utah, Vermont, Washington, West Virginia, and Wyoming. In an effort to assess the potential selection bias associated with the exclusion of these states, we conducted a t test to compare the mean change in SNAP receipt at the state level between states that were included in our analysis and states that were excluded. The results showed no significant difference in the mean change in SNAP use between these two groups of states (p = .80). In the absence of a clear cut method for imputing such a large amount of data, we elected to rely on “available case analysis,” which is advocated as the best approach for dealing with missing data in regression analysis, especially when statistical power is not an issue (Howell 2008).

  4. Defined by the Office of Management and Budget, a metropolitan (metro) area contains a core urban area of 50,000 or more population, and a micropolitan (micro) area contains an urban core of at least 10,000 (but less than 50,000) population. Each metro or micro area consists of one or more counties and includes the counties containing the core urban area as well as any adjacent counties that have a high degree of social and economic integration with the urban core (as measured by commuting to work). Non-core areas are counties that fit neither the metro nor micro definition. The index of dissimilarity measures the evenness with which two groups are distributed across component geographic areas (here census tracts) that make up a larger area (here counties). In cases where two groups are perfectly segregated, the index of dissimilarity takes the maximum value of 100. In cases where two groups are perfectly integrated, the index of dissimilarity takes the minimum value of zero (Racial Residential Segregation Measurement Project 2008).

  5. The spatial lag was produced by a “rook” weights matrix, which defines a location’s neighbors as those areas with shared borders. We use this method because it provides better model fit than the “queen” weights matrix, which is the other commonly used contiguity-based spatial weights measure.

  6. The adjusted R2 for each separate construct controlling for state-fixed effects is poverty experience .37; labor market conditions .43; population structure .36; human capital .36; and residential context .39.

References

  • Allard, S. W. (2009). Out of reach: Place, poverty, and the new American welfare state. New Haven, CT: Yale University Press.

    Google Scholar 

  • Bhattarai, G. R., Duffy, P. A., & Raymond, J. (2005). Use of food pantries and food stamps in low-income households in the United States. Journal of Consumer Affairs, 39, 276–298.

    Article  Google Scholar 

  • Congressional Budget Office. (2012). The Supplemental Nutrition Assistance Program. Accessed June 26, 2013, from www.cbo.gov/sites/default/files/cbofiles/attachments/04-19-SNAP.pdf.

  • Currie, J., & Tekin, E. (2011). Is there a link between foreclosure and health?. Cambridge, MA: National Bureau of Economic Research. Working Paper 17310.

    Book  Google Scholar 

  • DeNavas-Walt, C., Proctor, B. D., & Smith, J. C. (2011). Income, poverty, and health insurance coverage in the United States: 2010. US Census Bureau, Current Population Reports. Washington, DC: US Government Printing Office.

  • Figlio, D. N., Gundersen, C., & Ziliak, J. P. (2000). The effects of the macroeconomy and welfare reform on food stamp caseloads. American Journal of Agricultural Economics, 82, 635–641.

    Article  Google Scholar 

  • Fligstein, N., & Goldstein, A. (2011). The roots of the Great Recession. In D. B. Grusky, B. Western, & C. Wimer (Eds.), The Great Recession (pp. 21–55). New York: Russell Sage.

    Google Scholar 

  • Food and Nutrition Service. (2009). A short history of SNAP. Washington, DC: US Department of Agriculture. Accessed August 5, 2010, from http://www.fns.usda.gov/snaprules/Legislation/about.htm.

  • Food and Nutrition Service. (2011). The benefits of increasing Supplemental Nutrition Assistance Program (SNAP) participation in your state. Washington, DC: US Department of Agriculture. Accessed February 7, 2012, from www.fns.usda.gov/snap/outreach/pdfs/bc_facts.pdf.

  • Food and Nutrition Service. (2012). Supplemental Nutrition Assistance Program: State options report. Washington, DC: US Department of Agriculture.

    Google Scholar 

  • Food and Nutrition Service. (2013). Supplemental Nutrition Assistance Program: To apply… Washington, DC: US Department of Agriculture. Accessed June 26, 2013, from http://www.fns.usda.gov/ snap/applicant_recipients/apply.htm.

  • Frongillo, E. A., Jyoti, D. F., & Jones, S. J. (2006). Food Stamp Program participation is associated with better academic learning among school children. Journal of Nutrition, 136, 1077–1080.

    Google Scholar 

  • Gans, H. J. (2002). The Sociology of space: A use-centered view. City and Community, 1, 329–339.

    Article  Google Scholar 

  • Goetz, S. J., Rupasingha, A., & Zimmerman, J. N. (2004). Spatial Food Stamp Program participation dynamics in US counties. Review of Regional Studies, 34, 172–190.

    Google Scholar 

  • Grieger, L. D., & Danziger, S. H. (2011). Who receives food stamps during adulthood? Analyzing repeatable events with incomplete event histories. Demography, 48, 1601–1614.

    Article  Google Scholar 

  • Grusky, D. B., Western, B., & Wimer, C. (2011). The consequences of the Great Recession. In D. B. Grusky, B. Western, & C. Wimer (Eds.), The Great Recession (pp. 3–20). New York: Russell Sage.

    Google Scholar 

  • Gundersen, C., & Oliveira, V. (2001). The Food Stamp Program and food insufficiency. American Journal of Agricultural Economics, 83, 875–887.

    Article  Google Scholar 

  • Helfin, C., & Miller, K. (2012). The geography of need: identifying human service needs in rural America. Journal of Family Social Work, 15, 359–374.

    Article  Google Scholar 

  • Howell, D. C. (2008). The analysis of missing data. In W. Outhwaite & S. Turner (Eds.), Handbook of social science methodology. London: Sage.

    Google Scholar 

  • Kaminski, J. (2008). Trends in welfare caseloads. Washington, DC: The Urban Institute. Accesssed June 25, 2013, from www.urban.org/PDF/TANF_caseload.pdf.

  • Kwan, M. (2012). The uncertain geographic context problem. Annals of the Association of American Geographers, 102, 958–968.

    Article  Google Scholar 

  • Lobao, L. M. (2004). Continuity and change in place stratification: spatial inequality and middle-range territorial units. Rural Sociology, 69, 1–30.

    Article  Google Scholar 

  • Lobao, L. M., & Hooks, G. (2003). Public employment, welfare transfers, and economic well-being across local populations: Does a lean and mean government benefit the masses? Social Forces, 82, 519–556.

    Article  Google Scholar 

  • Lobao, L. M., & Hooks, G. (2007). Advancing the sociology of spatial inequality: spaces, places, and the subnational scale. In L. M. Lobao, G. Hooks, & A. R. Tickamyer (Eds.), The sociology of spatial inequality (pp. 29–61). Albany, NY: State University of New York.

    Google Scholar 

  • Lobao, L. M., Hooks, G., & Tickamyer, A. R. (2007). The sociology of spatial inequality. Albany, NY: State University of New York.

    Google Scholar 

  • Lobao, L. M., & Saenz, R. (2002). Spatial inequality and diversity as an emerging research area. Rural Sociology, 67, 497–511.

    Article  Google Scholar 

  • Logan, J. R. (2012). Making a place for space: Spatial thinking in social science. Annual Review of Sociology, 38, 507–524.

    Article  Google Scholar 

  • McLaughlin, D. K., Gardner, E. L., & Lichter, D. T. (1999). Economic restructuring and the changing prevalence of female-headed families in America. Rural Sociology, 64, 394–416.

    Article  Google Scholar 

  • Nathan, R. P. & Gais, T. L. (2001). Is devolution working? Federal and state roles in welfare. Washington DC: The Brookings Institution. Accessed August 9, 2010, from http://www.brookings.edu/articles/2001/summer_welfare_nathan.aspx.

  • National Bureau of Economic Research. (2012). US business cycle expansions and contractions. Accessed January 16, 2012, at: http://www.nber.org/cycles.html.

  • Nord, M. (2001). Food stamp participation and food security. Food Review, 24, 13–19.

    Google Scholar 

  • Racial Residential Segregation Measurement Project. (2008). “Residential segregation: what it is and how we measure it.” Accessed June 8, 2008, from http://enceladus.isr.umich.edu/race/seg.html.

  • Rank, M. R., & Hirschl, T. A. (2005). The likelihood of using food stamps during the adulthood years. Journal of Nutrition Education and Behavior, 37, 137–146.

    Article  Google Scholar 

  • Rosenbaum, D. (2013). SNAP is effective and efficient. Washington, DC: Center on Budget and Policy Priorities. Downloaded June 26, 2013 from http://www.cbpp.org/cms/?fa=view&id=3239.

  • Slack, T., & Myers, C. A. (2012). Understanding the geography of Food Stamp Program participation: Do space and place matter? Social Science Research, 41, 263–275.

    Article  Google Scholar 

  • Tapogna, J., Suter, A., Nord, M., & Leachman, M. (2004). Explaining variations in state hunger rates. Family Economic and Nutrition Review, 16, 12–21.

    Google Scholar 

  • Taylor, P., Kochhar, R., Frey, R., Velasco, G., & Motel, S. (2011). Twenty-to-one: Wealth gaps rise to record highs between whites, blacks, and Hispanics. Washington, DC: Pew Research Center.

    Google Scholar 

  • Tickamyer, A. R. (2000). Space matters! Spatial inequality in future sociology. Contemporary Sociology, 29, 805–813.

    Article  Google Scholar 

  • Van Hook, J., & Stamper Balistreri, K. (2006). Ineligible parents, eligible children: food stamp receipt, allotments, and food insecurity among children of immigrants. Social Science Research, 35, 228–251.

    Article  Google Scholar 

  • Voss, P. R. (2007). Demography as a spatial social science. Population Research and Policy Review, 26, 457–476.

    Article  Google Scholar 

  • Walden, M. L. (2012). Explaining the differences in state unemployment rates during the Great Recession. The Journal of Regional Analysis and Policy, 42, 251–257.

    Google Scholar 

  • Wallace, G., & Blank, R. M. (1999). What goes up must come down? Explaining recent changes in public assistance caseloads. In S. H. Danziger (Ed.), Economic conditions and welfare reform (pp. 49–89). Kalamazoo, MI: Upjohn Institute for Employment Research.

    Google Scholar 

  • Weisman, J. & Nixon, R. (2013). House Republicans push through farm bill, without food stamps. New York Times, July 12, 2013, A14.

  • Zedlewski, S. R., & Brauner, S. (1999). Declines in food stamp and welfare participation: Is there a connection?. Washington, DC: Urban Institute. Discussion Paper No. 99-13.

    Google Scholar 

Download references

Acknowledgments

This research was supported in part by the Research Innovation and Development Grants in Economics (RIDGE) Program administered by the Southern Rural Development Center (SRDC) and supported by the US Department of Agriculture (USDA), Economic Research Service (ERS).

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  1. Louisiana State University, 126 Stubbs Hall, Baton Rouge, LA, 70803, USA

    Tim Slack

  2. Pennington Biomedical Research Center, 6400 Perkins Road, Baton Rouge, LA, 70808, USA

    Candice A. Myers

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Correspondence to Tim Slack.

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Slack, T., Myers, C.A. The Great Recession and the Changing Geography of Food Stamp Receipt. Popul Res Policy Rev 33, 63–79 (2014). https://doi.org/10.1007/s11113-013-9310-9

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