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Does the Economy Explain the Explosion in the SNAP Caseload?


  • Danielson, Caroline
  • Klerman, Jacob Alex
  • Mejia, Marisol Cuellar


The Supplemental Nutrition Assistance Program (SNAP), which provides a monthly benefit to low-income families to help ensure an adequate and nutritious diet, has grown rapidly in recent years—by 50 percent in the seven years between 2000 and 2007 and by another 50 percent in the four years between 2007 and 2011—today serving 14 percent of the U.S. population. This paper makes three contributions to our understanding of the causes of this very rapid increase in the caseload: (i) extend the time period of analysis through and past the official end of the Great Recession, the most severe economic downturn since the Great Depression of the 1930s; (ii) analyze more geographically disaggregated caseloads and the impact of sub-state economic conditions; and (iii) relax the difference-in-differences assumption of common national year-to-year shifts allowing more robust estimates of the impact of the economy. Surprisingly, while one might have expected more geographically disaggregated data to improve the alignment of the measurement with the concept of interest (i.e., the labor market opportunities of an individual) and therefore lead to larger estimates of the impact of the economy, in fact estimates fall—perhaps due to measurement error. Indeed, in models that exploit sub-state level data, we find significant impacts of both the sub-state level and statewide economy on local area SNAP caseloads.

Suggested Citation

  • Danielson, Caroline & Klerman, Jacob Alex & Mejia, Marisol Cuellar, 2013. "Does the Economy Explain the Explosion in the SNAP Caseload?," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150558, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaea13:150558
    DOI: 10.22004/ag.econ.150558

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    References listed on IDEAS

    1. repec:mpr:mprres:6321 is not listed on IDEAS
    2. Wansbeek, Tom, 2001. "GMM estimation in panel data models with measurement error," Journal of Econometrics, Elsevier, vol. 104(2), pages 259-268, September.
    3. Lindo, Jason M., 2013. "Aggregation and the Estimated Effects of Local Economic Conditions on Health," IZA Discussion Papers 7396, Institute of Labor Economics (IZA).
    4. Nord, Mark & Prell, Mark, 2011. "Food Security Improved Following the 2009 ARRA Increase in SNAP Benefits," Economic Research Report 262242, United States Department of Agriculture, Economic Research Service.
    5. Griliches, Zvi & Hausman, Jerry A., 1986. "Errors in variables in panel data," Journal of Econometrics, Elsevier, vol. 31(1), pages 93-118, February.
    6. Hanson, Kenneth & Oliveira, Victor, 2012. "How Economic Conditions Affect Participation in USDA Nutrition Assistance Programs," Economic Information Bulletin 134682, United States Department of Agriculture, Economic Research Service.
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    Cited by:

    1. Pender, John & Jo, Young & Miller, Cristina, 2015. "Economic Impacts of Supplemental Nutrition Assistance Program Payments in Nonmetro vs. Metro Counties," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205626, Agricultural and Applied Economics Association.


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