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Can nutritional label use influence body weight outcomes?

Author

Listed:
  • Andreas Drichoutis

    (Department of Economics, University of Ioannina, Greece)

  • Rodolfo M. Nayga, Jr.

    (Department of Agricultural Economics & Agribusiness, University of Arkansas, USA)

  • Panagiotis Lazaridis

    (Department of Agricultural Economics & Rural Development, Agricultural University of Athens, Greece)

Abstract

Nutritional labeling has been of much interest to policy makers and health advocates due to rising obesity trends. So can nutritional label use really help reduce body weight outcomes? This study evaluates the impact of nutritional label use on body weight using the propensity score matching technique. We conducted a series of tests related to variable choice of the propensity score specification, quality of matching indicators, robustness checks, and sensitivity to unobserved heterogeneity using Rosenbaum bounds to validate our propensity score exercise. Our results generally suggest that nutritional label use does not affect body mass index. Implications of our findings are discussed.

Suggested Citation

  • Andreas Drichoutis & Rodolfo M. Nayga, Jr. & Panagiotis Lazaridis, 2009. "Can nutritional label use influence body weight outcomes?," Working Papers 2009-05, Agricultural University of Athens, Department Of Agricultural Economics.
    • Handle: RePEc:aua:wpaper:2009-05
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    References listed on IDEAS

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    Cited by:

    1. Georgia S. Papoutsi & Andreas C. Drichoutis & Rodolfo M. Nayga Jr., 2013. "The Causes Of Childhood Obesity: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 27(4), pages 743-767, September.
    2. Gong, Xuche & Yuan, Yan, 2017. "The Effect of School Transfers on Academic and Non-academic Performance of Rural-to-Urban Migrant Children in China," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 259178, Agricultural and Applied Economics Association.
    3. Fabrice Etilé, 2019. "The Economics of Diet and Obesity: Public Policy," Post-Print hal-02154445, HAL.
    4. Ran, Tao & Yue, Chengyan & Rihn, Alicia, 2015. "Are Grocery Shoppers of Households with Weight-Concerned Members Willing to Pay More for Nutritional Information on Food?," Journal of Food Distribution Research, Food Distribution Research Society, vol. 46(3), pages 1-18, November.
    5. Vinoles, Maria V. & You, Wen & Nayga, Rodolfo M. Jr., 2013. "Parental Nutrition Label Usage and Children's Dietary-related Outcomes," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 151274, Agricultural and Applied Economics Association.
    6. Di Fang & Michael R. Thomsen & Rodolfo M. Nayga & Aaron M. Novotny, 2019. "WIC Participation and Relative Quality of Household Food Purchases: Evidence from FoodAPS," Southern Economic Journal, John Wiley & Sons, vol. 86(1), pages 83-105, July.
    7. Anders, Sven & Schroeter, Christiane, 2015. "The Impact of Nutritional Supplement Choices on Diet Behavior and Obesity Outcomes," 2016 Allied Social Sciences Association (ASSA) Annual Meeting, January 3-5, 2016, San Francisco, California 212806, Agricultural and Applied Economics Association.
    8. Berning, Joshua P. & Chouinard, Hayley H. & Manning, Kenneth C. & McCluskey, Jill J. & Sprott, David E., 2010. "Identifying consumer preferences for nutrition information on grocery store shelf labels," Food Policy, Elsevier, vol. 35(5), pages 429-436, October.
    9. Choy, Christopher & Young, Ellie & Li, Megan & Cranor, Lorrie Faith & Peha, Jon M., 2024. "Consumer-driven design and evaluation of broadband labels," Telecommunications Policy, Elsevier, vol. 48(5).
    10. Schroeter, Christiane & Anders, Sven M., 2013. "Nutrition Label Usage, Diet Health Behavior, and Information Uncertainty," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 151214, Agricultural and Applied Economics Association.
    11. Edenbrandt, Anna Kristina & Smed, Sinne, 2018. "Exploring the correlation between self-reported preferences and actual purchases of nutrition labeled products," Food Policy, Elsevier, vol. 77(C), pages 71-80.
    12. Giorgio Brunello & Maria De Paola & Giovanna Labartino, 2012. "More Apples Less Chips? The Effect of School Fruit Schemes on the Consumption of Junk Food," ISER Discussion Paper 0840, Institute of Social and Economic Research, Osaka University.
    13. L. Behrenz & L. Delander & J. Månsson, 2016. "Is Starting a Business a Sustainable way out of Unemployment? Treatment Effects of the Swedish Start-up Subsidy," Journal of Labor Research, Springer, vol. 37(4), pages 389-411, December.
    14. D. Fang & R. M. Nayga & H. A. Snell & G. H. West & C. Bazzani, 2019. "Evaluating USA’s New Nutrition and Supplement Facts Label: Evidence from a Non-hypothetical Choice Experiment," Journal of Consumer Policy, Springer, vol. 42(4), pages 545-562, December.
    15. Brandon J. Restrepo, 2017. "Calorie Labeling in Chain Restaurants and Body Weight: Evidence from New York," Health Economics, John Wiley & Sons, Ltd., vol. 26(10), pages 1191-1209, October.
    16. Chang, Hung-Hao & Nayga Jr., Rodolfo M., 2011. "Mother's nutritional label use and children's body weight," Food Policy, Elsevier, vol. 36(2), pages 171-178, April.
    17. House, Lisa & Kim, Hyeyoung & Gao, Zhifeng & Rampersaud, Gail S., 2011. "Beverage Front of Package Nutrition Labels and Consumer Perception of Nutrition Information," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 109190, Agricultural and Applied Economics Association.
    18. Brunello, Giorgio & De Paola, Maria & Labartino, Giovanna, 2014. "More apples fewer chips? The effect of school fruit schemes on the consumption of junk food," Health Policy, Elsevier, vol. 118(1), pages 114-126.
    19. Ehmke, Mariah D. & Willson, Tina M. & Schroeter, Christiane & Hart, Ann Marie & Coupal, Roger H., 2009. "Obesity Economics for the Western United States," Western Economics Forum, Western Agricultural Economics Association, vol. 8(2), pages 1-13.

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    More about this item

    Keywords

    Nutritional Labels; Body Mass Index; Propensity Score Matching; sensitivity analysis;
    All these keywords.

    JEL classification:

    • I1 - Health, Education, and Welfare - - Health
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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