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An Empirical Analysis of Socio-Demographic Stratification in Sweetened Carbonated Soft-Drink Purchasing

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  • Rhodes, Charles

Abstract

Caloric soft drinks are the number one source of added sugars in U.S. diets, and are associated with many health problems. Three recent years of household purchase, household demographic, and industry advertising data allow Heckit estimation to identify how specific demographic groups vary in their purchase response to marketing of sweetened carbonated soft drinks (sCSDs) at the product category level. Empirical results reveal unique non-linear patterns of household purchase response to sCSD-industry price, sale, and advertising signals that vary significantly by specific demographic characteristics. Isolating the effects of either price, sale, or advertising on household purchase, highest education level of high school or less for the household head tends to be the most robust predictor of higher sCSD purchase, followed by household income at or below the poverty level for a family of four. The novel approach and results here contribute to the literature by estimating how rising education level for a fixed level of household income will variously affect sCSD purchase quantity depending on the ethnicity of the household, and does the same fixing education level across rising income level. Econometric controls are used to avoid estimation and inference errors the literature warns commonly accompany the Heckman specification.

Suggested Citation

  • Rhodes, Charles, 2012. "An Empirical Analysis of Socio-Demographic Stratification in Sweetened Carbonated Soft-Drink Purchasing," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124678, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaea12:124678
    DOI: 10.22004/ag.econ.124678
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    References listed on IDEAS

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    1. B. Douglas Bernheim & Antonio Rangel, 2004. "Addiction and Cue-Triggered Decision Processes," American Economic Review, American Economic Association, vol. 94(5), pages 1558-1590, December.
    2. Vartanian, L.R. & Schwartz, M.B. & Brownell, K.D., 2007. "Effects of soft drink consumption on nutrition and health: A systematic review and meta-analysis," American Journal of Public Health, American Public Health Association, vol. 97(4), pages 667-675.
    3. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    4. N/A, 1997. "Letter To Editor," Energy & Environment, , vol. 8(2), pages 177-177, June.
    5. Colin Vance, 2009. "Marginal effects and significance testing with Heckman's sample selection model: a methodological note," Applied Economics Letters, Taylor & Francis Journals, vol. 16(14), pages 1415-1419.
    6. Stevens-Garmon, John & Huang, Chung L. & Lin, Biing-Hwan, 2007. "Organic Demand: A Profile of Consumers in the Fresh Produce Market," Choices: The Magazine of Food, Farm, and Resource Issues, Agricultural and Applied Economics Association, vol. 22(2), pages 1-8.
    7. Robert H. Lustig & Laura A. Schmidt & Claire D. Brindis, 2012. "The toxic truth about sugar," Nature, Nature, vol. 482(7383), pages 27-29, February.
    8. repec:zbw:rwidps:0039 is not listed on IDEAS
    9. Sharma, L.L. & Teret, S.P. & Brownell, K.D., 2010. "The food industry and self-regulation: Standards to promote success and to avoid public health failures," American Journal of Public Health, American Public Health Association, vol. 100(2), pages 240-246.
    10. Chen Zhen & Justin L. Taylor & Mary K. Muth & Ephraim Leibtag, 2009. "Understanding Differences in Self-Reported Expenditures between Household Scanner Data and Diary Survey Data: A Comparison of Homescan and Consumer Expenditure Survey," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 31(3), pages 470-492, September.
    11. Cameron,A. Colin & Trivedi,Pravin K., 2005. "Microeconometrics," Cambridge Books, Cambridge University Press, number 9780521848053, November.
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    Keywords

    Agricultural and Food Policy; Consumer/Household Economics; Food Consumption/Nutrition/Food Safety;
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