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Preschool Children’s Demand for Sugar Sweetened Beverages: Evidence from Stated-Preference Panel Data

Author

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  • Ou Yang

    (Department of Econometrics and Business Statistics, Monash University)

  • Peter Sivey

    (Department of Economics and Finance, La Trobe University)

  • Andrea M. de Silva

    (Melbourne Dental School, The University of Melbourne)

  • Anthony Scott

    () (Melbourne Institute of Applied Economic and Social Research, The University of Melbourne)

Abstract

Consumption of sugar sweetened beverages exhibits strong associations with weight gain, obesity, and dental caries, especially in young children. The aim of this paper is to examine the impact of price changes on children’s consumption of sugar-sweetened beverages. Using micro-level panel data obtained from a stated preference experiment, we specify a two-sided censoring semi-parametric demand system model with fixed effects. To overcome an estimation difficulty that is potentially a common issue to all applications studying microlevel consumption data, we propose a new consistent two-step estimation framework. The economic restrictions implied by consumption theory are imposed through a consistent and asymptotically efficient GMM estimator. Our results show that the uncompensated own-price elasticities for sugar-sweetened beverages range from -0.83 to -0.94, demonstrating inelastic but substantial price effects. The marginal effects of demand with respect to nutritional attributes of sugar-sweetened beverages are negligible overall, but are strongest for those in low-income households. High-income households are less responsive to price and not responsive at all to non-price attributes.

Suggested Citation

  • Ou Yang & Peter Sivey & Andrea M. de Silva & Anthony Scott, 2016. "Preschool Children’s Demand for Sugar Sweetened Beverages: Evidence from Stated-Preference Panel Data," Melbourne Institute Working Paper Series wp2016n25, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    • Handle: RePEc:iae:iaewps:wp2016n25
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    File URL: http://melbourneinstitute.unimelb.edu.au/downloads/working_paper_series/wp2016n25.pdf
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    References listed on IDEAS

    as
    1. Steven T. Yen & Biing-Hwan Lin, 2006. "A Sample Selection Approach to Censored Demand Systems," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 88(3), pages 742-749.
    2. Hal R. Varian, 1983. "Non-parametric Tests of Consumer Behaviour," Review of Economic Studies, Oxford University Press, vol. 50(1), pages 99-110.
    3. Deaton, Angus & Irish, Margaret, 1984. "Statistical models for zero expenditures in household budgets," Journal of Public Economics, Elsevier, vol. 23(1-2), pages 59-80.
    4. Powell, James L, 1986. "Symmetrically Trimmed Least Squares Estimation for Tobit Models," Econometrica, Econometric Society, vol. 54(6), pages 1435-1460, November.
    5. Chen Zhen & Michael K. Wohlgenant & Shawn Karns & Phillip Kaufman, 2010. "Habit Formation and Demand for Sugar-Sweetened Beverages," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(1), pages 175-193.
    6. Wales, T. J. & Woodland, A. D., 1983. "Estimation of consumer demand systems with binding non-negativity constraints," Journal of Econometrics, Elsevier, vol. 21(3), pages 263-285, April.
    7. Jason M. Fletcher & David Frisvold & Nathan Tefft, 2010. "Can Soft Drink Taxes Reduce Population Weight?," Contemporary Economic Policy, Western Economic Association International, vol. 28(1), pages 23-35, January.
    8. Steven T. Yen & Biing-Hwan Lin & David M. Smallwood, 2003. "Quasi- and Simulated-Likelihood Approaches to Censored Demand Systems: Food Consumption by Food Stamp Recipients in the United States," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(2), pages 458-478.
    9. Heien, Dale & Wessells, Cathy Roheim, 1990. "Demand Systems Estimation with Microdata: A Censored Regression Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(3), pages 365-371, July.
    10. Nayga, Rodolfo M., Jr., 1995. "Determinants Of U.S. Household Expenditures On Fruit And Vegetables: A Note And Update," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 27(2), pages 1-7, December.
    11. Giancarlo Moschini, 1995. "Units of Measurement and the Stone Index in Demand System Estimation," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(1), pages 63-68.
    12. Fabrice Etilé & Anurag Sharma, 2015. "Do High Consumers of Sugar‐Sweetened Beverages Respond Differently to Price Changes? A Finite Mixture IV‐Tobit Approach," Health Economics, John Wiley & Sons, Ltd., vol. 24(9), pages 1147-1163, September.
    13. Diansheng Dong & Harry M. Kaiser & Øystein Myrland, 2007. "Quantity and quality effects of advertising: a demand system approach," Agricultural Economics, International Association of Agricultural Economists, vol. 36(3), pages 313-324, May.
    14. Diansheng Dong & Christopher G. Davis & Hayden Stewart, 2015. "The quantity and variety of households’ meat purchases: A censored demand system approach," Agricultural Economics, International Association of Agricultural Economists, vol. 46(1), pages 99-112, January.
    15. Chalfant, James A, 1987. "A Globally Flexible, Almost Ideal Demand System," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(2), pages 233-242, April.
    16. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
    17. Gallant, A. Ronald, 1981. "On the bias in flexible functional forms and an essentially unbiased form : The fourier flexible form," Journal of Econometrics, Elsevier, vol. 15(2), pages 211-245, February.
    18. Scott, Anthony & Witt, Julia & Humphreys, John & Joyce, Catherine & Kalb, Guyonne & Jeon, Sung-Hee & McGrail, Matthew, 2013. "Getting doctors into the bush: General Practitioners' preferences for rural location," Social Science & Medicine, Elsevier, vol. 96(C), pages 33-44.
    19. Alan Sule & Honoré Bo E. & Hu Luojia & Leth-Petersen Søren, 2014. "Estimation of Panel Data Regression Models with Two-Sided Censoring or Truncation," Journal of Econometric Methods, De Gruyter, vol. 3(1), pages 1-20, January.
    20. Blundell, Richard & Pashardes, Panos & Weber, Guglielmo, 1993. "What Do We Learn About Consumer Demand Patterns from Micro Data?," American Economic Review, American Economic Association, vol. 83(3), pages 570-597, June.
    21. Adolf Buse, 1998. "Testing Homogeneity in the Linearized Almost Ideal Demand System," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(1), pages 208-220.
    22. Federico Perali & Jean-Paul Chavas, 2000. "Estimation of Censored Demand Equations from Large Cross-Section Data," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 82(4), pages 1022-1037.
    23. Capps Jr., Oral & Church, Jeffrey & Alan Love, H., 2003. "Specification issues and confidence intervals in unilateral price effects analysis," Journal of Econometrics, Elsevier, vol. 113(1), pages 3-31, March.
    24. David E. Sahn, 2005. "Consistent Estimation of Censored Demand Systems Using Panel Data," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(3), pages 660-672.
    25. Haag, Berthold R. & Hoderlein, Stefan & Pendakur, Krishna, 2009. "Testing and imposing Slutsky symmetry in nonparametric demand systems," Journal of Econometrics, Elsevier, vol. 153(1), pages 33-50, November.
    26. Wooldridge, Jeffrey M., 1995. "Selection corrections for panel data models under conditional mean independence assumptions," Journal of Econometrics, Elsevier, vol. 68(1), pages 115-132, July.
    27. Steven T. Yen, 2005. "A Multivariate Sample-Selection Model: Estimating Cigarette and Alcohol Demands with Zero Observations," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(2), pages 453-466.
    28. Andreyeva, T. & Long, M.W. & Brownell, K.D., 2010. "The impact of food prices on consumption: A systematic review of research on the price elasticity of demand for food," American Journal of Public Health, American Public Health Association, vol. 100(2), pages 216-222.
    29. Alain Carpentier & Hervé Guyomard, 2001. "Unconditional Elasticities in Two-Stage Demand Systems: An Approximate Solution," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(1), pages 222-229.
    30. Arthur Lewbel, 1989. "Identification and Estimation of Equivalence Scales under Weak Separability," Review of Economic Studies, Oxford University Press, vol. 56(2), pages 311-316.
    31. Manser, Marilyn E & McDonald, Richard J, 1988. "An Analysis of Substitution Bias in Measuring Inflation, 1959-85," Econometrica, Econometric Society, vol. 56(4), pages 909-930, July.
    32. Finkelstein, Eric A. & Zhen, Chen & Bilger, Marcel & Nonnemaker, James & Farooqui, Assad M. & Todd, Jessica E., 2013. "Implications of a sugar-sweetened beverage (SSB) tax when substitutions to non-beverage items are considered," Journal of Health Economics, Elsevier, vol. 32(1), pages 219-239.
    33. David L. Edgerton, 1997. "Weak Separability and the Estimation of Elasticities in Multistage Demand Systems," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(1), pages 62-79.
    34. Hoderlein, Stefan & Mihaleva, Sonya, 2008. "Increasing the price variation in a repeated cross section," Journal of Econometrics, Elsevier, vol. 147(2), pages 316-325, December.
    35. Fifer, Simon & Rose, John M., 2016. "Can you ever be certain? Reducing hypothetical bias in stated choice experiments via respondent reported choice certaintyAuthor-Name: Beck, Matthew J," Transportation Research Part B: Methodological, Elsevier, vol. 89(C), pages 149-167.
    36. Anurag Sharma & Katharina Hauck & Bruce Hollingsworth & Luigi Siciliani, 2014. "The Effects Of Taxing Sugar‐Sweetened Beverages Across Different Income Groups," Health Economics, John Wiley & Sons, Ltd., vol. 23(9), pages 1159-1184, September.
    37. Vella, F, 1992. "Simple Tests for Sample Selection Bias in Censored and Discrete Choice Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(4), pages 413-421, Oct.-Dec..
    38. Fredrik Carlsson & Peter Martinsson, 2003. "Design techniques for stated preference methods in health economics," Health Economics, John Wiley & Sons, Ltd., vol. 12(4), pages 281-294, April.
    39. Arndt, Channing, 1999. "Demand For Herbicide In Corn: An Entropy Approach Using Micro-Level Data," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 24(1), pages 1-18, July.
    40. Steven Yen & Kamhon Kan & Shew-Jiuan Su, 2002. "Household demand for fats and oils: two-step estimation of a censored demand system," Applied Economics, Taylor & Francis Journals, vol. 34(14), pages 1799-1806.
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    Cited by:

    1. Blake, Miranda R. & Lancsar, Emily & Peeters, Anna & Backholer, Kathryn, 2019. "Sugar-sweetened beverage price elasticities in a hypothetical convenience store," Social Science & Medicine, Elsevier, vol. 225(C), pages 98-107.

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