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The Supplemental Nutrition Assistance Program and Childhood Obesity in the United States: Evidence from the National Longitudinal Survey of Youth 1997

Author

Listed:
  • Maoyong Fan

    (Ball State University)

  • Yanhong Jin

    (Rutgers University)

Abstract

Using the National Longitudinal Survey of Youth 1997, this paper employs difference-in-difference propensity score matching to examine whether the Supplemental Nutrition Assistance Program (SNAP) contributes to childhood obesity. We find no statistically significant SNAP effect among the 12- to 20-year-old participants when controlling for selection bias and more accurately defining the treatment and comparison groups. The results are robust to various robustness checks including redefining the treatment and comparison groups by excluding those who previously enrolled in the SNAP, using an alternative treatment definition based on SNAP benefits received, using different specifications of the propensity score equation, and employing different estimation techniques (covariate matching and inverse probability weighting). The robustness analyses regarding unobservables also find no statistically significant SNAP effects. This study differs from previous research in three major aspects. First, we carefully examine the intensity of SNAP participation (full-time versus part-time) and the amount of SNAP benefits received for one-, two-, and three-year durations. Second, we focus on the change in the BMI (body mass index) or the obesity status rather than the level and control for the pretreatment BMI to avoid the confounding effects of the time-invariant factors. Third, instead of making parametric assumptions on the outcomes, we employ a variety of semiparametric estimators to control for the selection bias of program participation. The results show that the SNAP is not responsible for the higher prevalence of obesity among adolescents of low-income households. Proposed SNAP changes such as more frequent benefit distribution and a focus on fresh fruits and vegetables are likely to be ineffective in reducing childhood obesity, although they might encourage healthy dietary practices among SNAP participants.

Suggested Citation

  • Maoyong Fan & Yanhong Jin, 2015. "The Supplemental Nutrition Assistance Program and Childhood Obesity in the United States: Evidence from the National Longitudinal Survey of Youth 1997," American Journal of Health Economics, MIT Press, vol. 1(4), pages 432-460, Fall.
  • Handle: RePEc:tpr:amjhec:v:1:y:2015:i:4:p:432-460
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    References listed on IDEAS

    as
    1. LaLonde, Robert J, 1986. "Evaluating the Econometric Evaluations of Training Programs with Experimental Data," American Economic Review, American Economic Association, vol. 76(4), pages 604-620, September.
    2. Hilary W. Hoynes & Diane Whitmore Schanzenbach, 2009. "Consumption Responses to In-Kind Transfers: Evidence from the Introduction of the Food Stamp Program," American Economic Journal: Applied Economics, American Economic Association, vol. 1(4), pages 109-139, October.
    3. Pedro Carneiro & Costas Meghir & Matthias Parey, 2013. "Maternal Education, Home Environments, And The Development Of Children And Adolescents," Journal of the European Economic Association, European Economic Association, vol. 11, pages 123-160, January.
    4. A. Smith, Jeffrey & E. Todd, Petra, 2005. "Does matching overcome LaLonde's critique of nonexperimental estimators?," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 305-353.
    5. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
    6. Robert Breunig & Indraneel Dasgupta, 2005. "Do Intra-Household Effects Generate the Food Stamp Cash-Out Puzzle?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(3), pages 552-568.
    7. Black, Dan A. & Smith, J.A.Jeffrey A., 2004. "How robust is the evidence on the effects of college quality? Evidence from matching," Journal of Econometrics, Elsevier, vol. 121(1-2), pages 99-124.
    8. repec:fth:prinin:468 is not listed on IDEAS
    9. Andrews,Donald W. K. & Stock,James H. (ed.), 2005. "Identification and Inference for Econometric Models," Cambridge Books, Cambridge University Press, number 9780521844413.
    10. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2003. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometrica, Econometric Society, vol. 71(4), pages 1161-1189, July.
    11. Zagorsky, Jay L. & Smith, Patricia K., 2009. "Does the U.S. Food Stamp Program contribute to adult weight gain?," Economics & Human Biology, Elsevier, vol. 7(2), pages 246-258, July.
    12. Rajeev H. Dehejia & Sadek Wahba, 1998. "Causal Effects in Non-Experimental Studies: Re-Evaluating the Evaluation of Training Programs," NBER Working Papers 6586, National Bureau of Economic Research, Inc.
    13. Alberto Abadie & David Drukker & Jane Leber Herr & Guido W. Imbens, 2004. "Implementing matching estimators for average treatment effects in Stata," Stata Journal, StataCorp LP, vol. 4(3), pages 290-311, September.
    14. 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.
    15. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    16. 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), pages 1-14, April.
    17. Diane Whitmore, 2002. "What Are Food Stamps Worth?," Working Papers 847, Princeton University, Department of Economics, Industrial Relations Section..
    18. Stock, James H & Wright, Jonathan H & Yogo, Motohiro, 2002. "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 518-529, October.
    19. Chad D. Meyerhoefer & Muzhe Yang, 2011. "The Relationship between Food Assistance and Health: A Review of the Literature and Empirical Strategies for Identifying Program Effects," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 33(3), pages 304-344.
    20. Kaushal, N., 2007. "Do food stamps cause obesity?: Evidence from immigrant experience," Journal of Health Economics, Elsevier, vol. 26(5), pages 968-991, September.
    21. Case, Anne & Fertig, Angela & Paxson, Christina, 2005. "The lasting impact of childhood health and circumstance," Journal of Health Economics, Elsevier, vol. 24(2), pages 365-389, March.
    22. Jinyong Hahn, 1998. "On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects," Econometrica, Econometric Society, vol. 66(2), pages 315-332, March.
    23. Jeffrey Smith, 2000. "A Critical Survey of Empirical Methods for Evaluating Active Labor Market Policies," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 136(III), pages 247-268, September.
    24. Alberto Abadie & Guido W. Imbens, 2002. "Simple and Bias-Corrected Matching Estimators for Average Treatment Effects," NBER Technical Working Papers 0283, National Bureau of Economic Research, Inc.
    25. Robert A. Moffitt, 2003. "Means-Tested Transfer Programs in the United States," NBER Books, National Bureau of Economic Research, Inc, number moff03-1, March.
    26. Diane Whitmore, 2002. "What Are Food Stamps Worth?," Working Papers 847, Princeton University, Department of Economics, Industrial Relations Section..
    27. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
    28. Maximilian D. Schmeiser, 2012. "The impact of long‐term participation in the supplemental nutrition assistance program on child obesity," Health Economics, John Wiley & Sons, Ltd., vol. 21(4), pages 386-404, April.
    29. Maoyong Fan, 2010. "Do Food Stamps Contribute to Obesity in Low-Income Women? Evidence from the National Longitudinal Survey of Youth 1979," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(4), pages 1165-1180.
    30. Zhiqiang Tan, 2010. "Bounded, efficient and doubly robust estimation with inverse weighting," Biometrika, Biometrika Trust, vol. 97(3), pages 661-682.
    31. Parke E. Wilde & Christine K. Ranney, 2000. "The Monthly Food Stamp Cycle: Shooping Frequency and Food Intake Decisions in an Endogenous Switching Regression Framework," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 82(1), pages 200-213.
    32. 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), pages 1-6.
    33. Wooldridge, Jeffrey M., 2007. "Inverse probability weighted estimation for general missing data problems," Journal of Econometrics, Elsevier, vol. 141(2), pages 1281-1301, December.
    34. Shapiro, Jesse M., 2005. "Is there a daily discount rate? Evidence from the food stamp nutrition cycle," Journal of Public Economics, Elsevier, vol. 89(2-3), pages 303-325, February.
    35. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(2), pages 261-294.
    36. Caroline Ratcliffe & Signe-Mary McKernan & Sisi Zhang, 2011. "How Much Does the Supplemental Nutrition Assistance Program Reduce Food Insecurity?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(4), pages 1082-1098.
    37. Janet Currie, 2003. "US Food and Nutrition Programs," NBER Chapters, in: Means-Tested Transfer Programs in the United States, pages 199-290, National Bureau of Economic Research, Inc.
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    More about this item

    Keywords

    American; health; health economics; health policy; incentives; health behaviors; health care; survey; SNAP; childhood obesity;
    All these keywords.

    JEL classification:

    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

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