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Measuring the Impact of Nutrition Labels on Food Purchasing Decisions: A field experiment with scanner data

Author

Listed:
  • Joshua P. Berning

    (University of Connecticut)

  • Hayley H. Chouinard

    (Washington State University)

  • Jill J. McCluskey

    (Washington State University)

Abstract

A simple experiment is used to examine the effect of grocery store nutrition labels on the sales of microwave popcorn in the East Bay area of California. Using an incomplete demand system we estimate the impact of the nutrition labels on sales of healthy (products that merit a nutrition label) and unhealthy (products that do not merit a nutrition label) microwave popcorn. Contrary to expectations, we find that nutrition labels decrease sales of healthy popcorn and increase sales of unhealthy popcorn across all stores. We speculate that nutrition labels on popcorn may signal unwanted product characteristics such as undesirable taste. Our findings highlight unintended effects created by nutrition labels. In terms of public welfare, it is important to consider not just the content of private industry nutrition labels but the effect they have on consumer behavior.

Suggested Citation

  • Joshua P. Berning & Hayley H. Chouinard & Jill J. McCluskey, 2009. "Measuring the Impact of Nutrition Labels on Food Purchasing Decisions: A field experiment with scanner data," Food Marketing Policy Center Research Reports 117, University of Connecticut, Department of Agricultural and Resource Economics, Charles J. Zwick Center for Food and Resource Policy.
    • Handle: RePEc:zwi:fpcrep:117
    as

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    File URL: http://fmpc.uconn.edu/publications/rr/rr117.pdf
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    References listed on IDEAS

    as
    1. Hayley H. Chouinard & David E. Davis & Jeffrey T. LaFrance & Jeffrey M. Perloff, 2010. "Milk Marketing Order Winners and Losers," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 32(1), pages 59-76.
    2. Jeffrey H. Dorfman & Catherine L. Kling & Richard J. Sexton, 1990. "Confidence Intervals for Elasticities and Flexibilities: Reevaluating the Ratios of Normals Case," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 72(4), pages 1006-1017.
    3. Jeffrey T. LaFrance, 1990. "Incomplete Demand Systems And Semilogarithmic Demand Models," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 34(2), pages 118-131, August.
    4. Mario F. Teisl & Nancy E. Bockstael & Alan Levy, 2001. "Measuring the Welfare Effects of Nutrition Information," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(1), pages 133-149.
    5. Foster, William & Just, Richard E., 1989. "Measuring welfare effects of product contamination with consumer uncertainty," Journal of Environmental Economics and Management, Elsevier, vol. 17(3), pages 266-283, November.
    6. LaFrance, Jeffrey T., 2004. "Integrability of the linear approximate almost ideal demand system," Economics Letters, Elsevier, vol. 84(3), pages 297-303, September.
    7. Dorfman, Jeffrey H. & Kling, Catherine L. & Sexton, Richard J., 1990. "Confidence Intervals for Elasticities and Flexibilities," 1990 Annual meeting, August 5-8, Vancouver, Canada 270866, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
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