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Does the Food Stamp Program Really Increase Obesity? The Importance of Accounting for Misclassification Errors

Author

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  • Vassilopoulos, Achilleas
  • Drichoutis, Andreas
  • Nayga, Rodolfo
  • Lazaridis, Panagiotis

Abstract

Over the last few decades, the prevalence of obesity among US citizens has grown rapidly, especially among low-income individuals. This has led to questions about the effectiveness of nutritional assistance programs such as the Supplemental Nutrition Assistance Program (SNAP), formerly known as the Food Stamps Program (FSP). Results from previous studies generally suggest that FSP participation increases obesity. This finding is however based on analyses that assumed that participants do not misclassify their program participation. Significant misclassification errors have been reported in the literature. Using propensity score matching estimation and a new method to conduct extensive sensitivity analysis, we find that this finding is quite sensitive to misclassification errors above 10% and to functional form assumptions.

Suggested Citation

  • Vassilopoulos, Achilleas & Drichoutis, Andreas & Nayga, Rodolfo & Lazaridis, Panagiotis, 2011. "Does the Food Stamp Program Really Increase Obesity? The Importance of Accounting for Misclassification Errors," MPRA Paper 28768, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:28768
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    References listed on IDEAS

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    1. Donald B. Rubin, 2003. "Nested multiple imputation of NMES via partially incompatible MCMC," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 57(1), pages 3-18, February.
    2. Andrea Ichino & Fabrizia Mealli & Tommaso Nannicini, 2008. "From temporary help jobs to permanent employment: what can we learn from matching estimators and their sensitivity?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(3), pages 305-327.
    3. Joshua D. Angrist & Jörn-Steffen Pischke, 2010. "The Credibility Revolution in Empirical Economics: How Better Research Design Is Taking the Con out of Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 24(2), pages 3-30, Spring.
    4. Millimet, Daniel L. & Tchernis, Rusty, 2009. "On the Specification of Propensity Scores, With Applications to the Analysis of Trade Policies," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(3), pages 397-415.
    5. Kaushal, N., 2007. "Do food stamps cause obesity?: Evidence from immigrant experience," Journal of Health Economics, Elsevier, vol. 26(5), pages 968-991, September.
    6. James Heckman & Salvador Navarro-Lozano, 2004. "Using Matching, Instrumental Variables, and Control Functions to Estimate Economic Choice Models," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 30-57, February.
    7. David M. Cutler & Edward L. Glaeser & Jesse M. Shapiro, 2003. "Why Have Americans Become More Obese?," Journal of Economic Perspectives, American Economic Association, vol. 17(3), pages 93-118, Summer.
    8. Odelia Rosin, 2008. "The Economic Causes Of Obesity: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 22(4), pages 617-647, September.
    9. Darius Lakdawalla & Tomas Philipson & Jay Bhattacharya, 2005. "Welfare-Enhancing Technological Change and the Growth of Obesity," American Economic Review, American Economic Association, vol. 95(2), pages 253-257, May.
    10. Baum, Charles, 2007. "The Effects of Food Stamps on Obesity," Contractor and Cooperator Reports 292009, United States Department of Agriculture, Economic Research Service.
    11. 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.
    12. Charles L. Baum, 2011. "The Effects of Food Stamps on Obesity," Southern Economic Journal, John Wiley & Sons, vol. 77(3), pages 623-651, January.
    13. Zhuo Chen & Steven T. Yen & David B. Eastwood, 2005. "Effects of Food Stamp Participation on Body Weight and Obesity," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(5), pages 1167-1173.
    14. Alberto Abadie & Guido W. Imbens, 2006. "Large Sample Properties of Matching Estimators for Average Treatment Effects," Econometrica, Econometric Society, vol. 74(1), pages 235-267, January.
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    Cited by:

    1. Lorenzo Almada & Ian McCarthy & Rusty Tchernis, 2016. "What Can We Learn about the Effects of Food Stamps on Obesity in the Presence of Misreporting?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(4), pages 997-1017.
    2. Almada, Lorenzo & McCarthy, Ian M., 2017. "It's a cruel summer: Household responses to reductions in government nutrition assistance," Journal of Economic Behavior & Organization, Elsevier, vol. 143(C), pages 45-57.

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    More about this item

    Keywords

    matching estimators; sensitivity analysis; food stamps; obesity;
    All these keywords.

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • I10 - Health, Education, and Welfare - - Health - - - General

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