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Identifying the Effects of SNAP (Food Stamps) on Child Health Outcomes When Participation Is Endogenous and Misreported

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  • Brent Kreider
  • John V. Pepper
  • Craig Gundersen
  • Dean Jolliffe

Abstract

The literature assessing the efficacy of the Supplemental Nutrition Assistance Program (SNAP), formerly known as the Food Stamp Program, has long puzzled over positive associations between SNAP receipt and various undesirable health outcomes such as food insecurity. Assessing the causal impacts of SNAP, however, is hampered by two key identification problems: endogenous selection into participation and extensive systematic underreporting of participation status. Using data from the National Health and Nutrition Examination Survey (NHANES), we extend partial identification bounding methods to account for these two identification problems in a single unifying framework. Specifically, we derive informative bounds on the average treatment effect (ATE) of SNAP on child food insecurity, poor general health, obesity, and anemia across a range of different assumptions used to address the selection and classification error problems. In particular, to address the selection problem, we apply relatively weak nonparametric assumptions on the latent outcomes, selected treatments, and observed covariates. To address the classification error problem, we formalize a new approach that uses auxiliary administrative data on the size of the SNAP caseload to restrict the magnitudes and patterns of SNAP reporting errors. Layering successively stronger assumptions, an objective of our analysis is to make transparent how the strength of the conclusions varies with the strength of the identifying assumptions. Under the weakest restrictions, there is substantial ambiguity; we cannot rule out the possibility that SNAP increases or decreases poor health. Under stronger but plausible assumptions used to address the selection and classification error problems, we find that commonly cited relationships between SNAP and poor health outcomes provide a misleading picture about the true impacts of the program. Our tightest bounds identify favorable impacts of SNAP on child health.

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File URL: http://hdl.handle.net/10.1080/01621459.2012.682828
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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Journal of the American Statistical Association.

Volume (Year): 107 (2012)
Issue (Month): 499 (September)
Pages: 958-975

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Handle: RePEc:taf:jnlasa:v:107:y:2012:i:499:p:958-975

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References

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  1. Hilary W. Hoynes & Diane Whitmore Schanzenbach, 2007. "Consumption Reponses to In-Kind Transfers: Evidence from the Introduction of the Food Stamp Program," Working Papers 0711, Harris School of Public Policy Studies, University of Chicago.
  2. Neeraj Kaushal, 2007. "Do Food Stamps Cause Obesity? Evidence from Immigrant Experience," NBER Working Papers 12849, National Bureau of Economic Research, Inc.
  3. John V. Pepper, 2000. "The Intergenerational Transmission Of Welfare Receipt: A Nonparametric Bounds Analysis," The Review of Economics and Statistics, MIT Press, vol. 82(3), pages 472-488, August.
  4. Anne Case & Darren Lubotsky & Christina Paxson, 2002. "Economic Status and Health in Childhood: The Origins of the Gradient," American Economic Review, American Economic Association, vol. 92(5), pages 1308-1334, December.
  5. Molinari, Francesca, 2010. "Missing Treatments," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 82-95.
  6. Janet Currie, 2003. "U.S. Food and Nutrition Programs," NBER Chapters, in: Means-Tested Transfer Programs in the United States, pages 199-290 National Bureau of Economic Research, Inc.
  7. Moffitt, Robert, 1983. "An Economic Model of Welfare Stigma," American Economic Review, American Economic Association, vol. 73(5), pages 1023-35, December.
  8. Charles F. Manski & John V. Pepper, 1998. "Monotone Instrumental Variables with an Application to the Returns to Schooling," NBER Technical Working Papers 0224, National Bureau of Economic Research, Inc.
  9. Nord, Mark & Andrews, Margaret S. & Carlson, Steven, 2008. "Household Food Security in the United States, 2007," Economic Research Report 56483, United States Department of Agriculture, Economic Research Service.
  10. Meyerhoefer, Chad D. & Pylypchuk, Vuriy, 2008. "AJAE Appendix: Does Participation in the Food Stamp Program Increase the Prevalence of Obesity and Health Care Spending?," American Journal of Agricultural Economics Appendices, Agricultural and Applied Economics Association, vol. 90(2), May.
  11. Guido Imbens & Charles F. Manski, 2003. "Confidence intervals for partially identified parameters," CeMMAP working papers CWP09/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  12. Bhattacharya, Jayanta & Currie, Janet & Haider, Steven, 2004. "Poverty, food insecurity, and nutritional outcomes in children and adults," Journal of Health Economics, Elsevier, vol. 23(4), pages 839-862, July.
  13. Craig Gundersen & Susan Offutt, 2005. "Farm Poverty and Safety Nets," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(4), pages 885-899.
  14. repec:att:wimass:9604 is not listed on IDEAS
  15. Kreider, Brent & Hill, Steven C., 2005. "Partially Identifying Treatment Effects with an Application to Covering the Uninsured," Staff General Research Papers 12296, Iowa State University, Department of Economics.
  16. Kreider, Brent & Pepper, John V., 2003. "Inferring Disability Status from Corrupt Data," Staff General Research Papers 10228, Iowa State University, Department of Economics.
  17. Kreider, Brent & Pepper, John V., 2003. "Disability and Employment: Reevaluating the Evidence in Light of Reporting Errors," Staff General Research Papers 10229, Iowa State University, Department of Economics.
  18. Charles F. Manski, 1997. "Monotone Treatment Response," Econometrica, Econometric Society, vol. 65(6), pages 1311-1334, November.
  19. Craig Gundersen & Victor Oliveira, 2001. "The Food Stamp Program and Food Insufficiency," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(4), pages 875-887.
  20. Bollinger, Christopher R., 1996. "Bounding mean regressions when a binary regressor is mismeasured," Journal of Econometrics, Elsevier, vol. 73(2), pages 387-399, August.
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Citations

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Cited by:
  1. Manan Roy & Daniel Millimet & Rusty Tchernis, 2012. "Federal nutrition programs and childhood obesity: inside the black box," Review of Economics of the Household, Springer, vol. 10(1), pages 1-38, March.
  2. Stefanie Hof, 2014. "Does Private Tutoring Work? The Effectiveness of Private Tutoring: A Nonparametric Bounds Analysis," Economics of Education Working Paper Series 0096, University of Zurich, Institute for Strategy and Business Economics (ISU).
  3. Burgstahler, Rebecca & Gundersen, Craig & Garasky, Steven B., 2012. "The Supplemental Nutrition Assistance Program, Financial Stress, and Childhood Obesity," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 41(1), April.
  4. Manan Roy, 2012. "Identifying the Effect of WIC on Infant Health When Participation is Endogenous and Misreported," Departmental Working Papers 1202, Southern Methodist University, Department of Economics.
  5. Gundersen, Craig & Kreider, Brent, 2009. "Bounding the effects of food insecurity on children's health outcomes," Journal of Health Economics, Elsevier, vol. 28(5), pages 971-983, September.
  6. Lafférs, Lukáš, 2013. "A note on bounding average treatment effects," Economics Letters, Elsevier, vol. 120(3), pages 424-428.
  7. Wooyoung Kim & Koohyun Kwon & Soonwoo Kwon & Sokbae 'Simon' Lee, 2014. "The identification power of smoothness assumptions in models with counterfactual outcomes," CeMMAP working papers CWP17/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  8. Peckham, Janet G. & Kropp, Jaclyn D., 2012. "Are National School Lunch Program Participants More Likely to be Obese? Dealing with Identification," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124905, Agricultural and Applied Economics Association.

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