IDEAS home Printed from https://ideas.repec.org/a/eee/ehbiol/v38y2020ics1570677x1930276x.html
   My bibliography  Save this article

Is the public sweet on sugary beverages? Social desirability bias and sweetened beverage taxes

Author

Listed:
  • Knox, Melissa A.
  • Oddo, Vanessa M.
  • Walkinshaw, Lina Pinero
  • Jones-Smith, Jessica

Abstract

Social desirability bias has been documented in self-reported diet as well as in voting behavior, but not in regards to sweetened beverage consumption or sweetened beverage taxes. We find evidence that respondents in a mixed-mode opinion survey exhibit social desirability bias in both reported sweetened beverage consumption and beliefs about the health and economic benefits of sweetened beverage taxes. We do so in a study of 1704 adults residing in Seattle, Minneapolis, and the D.C. metro area. Phone respondents in our survey under-report sweetened beverage consumption by 0.63 beverages per week relative to web respondents (average web respondent consumption is 3.55 beverages per week). They also over-report their beliefs about the positive health and economic impacts of sweetened beverage taxes by 0.54 points in an 18-point index (average web respondent index score is 2.79). These differences are measured after we control for selection into survey mode by using matching methods, and we interpret them as occurring due to social desirability bias. In contrast to these findings, there is no modal difference in respondents’ stated approval of sweetened beverage taxes, and so we conclude that this question is not subject to social desirability bias.

Suggested Citation

  • Knox, Melissa A. & Oddo, Vanessa M. & Walkinshaw, Lina Pinero & Jones-Smith, Jessica, 2020. "Is the public sweet on sugary beverages? Social desirability bias and sweetened beverage taxes," Economics & Human Biology, Elsevier, vol. 38(C).
    • Handle: RePEc:eee:ehbiol:v:38:y:2020:i:c:s1570677x1930276x
    DOI: 10.1016/j.ehb.2020.100886
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1570677X1930276X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ehb.2020.100886?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Cattaneo, Matias D., 2010. "Efficient semiparametric estimation of multi-valued treatment effects under ignorability," Journal of Econometrics, Elsevier, vol. 155(2), pages 138-154, April.
    2. Burke, Mary A. & Carman, Katherine G., 2017. "You can be too thin (but not too tall): Social desirability bias in self-reports of weight and height," Economics & Human Biology, Elsevier, vol. 27(PA), pages 198-222.
    3. Matias D. Cattaneo, 2010. "multi-valued treatment effects," The New Palgrave Dictionary of Economics,, Palgrave Macmillan.
    4. Grewenig, Elisabeth & Lergetporer, Philipp & Simon, Lisa & Werner, Katharina & Woessmann, Ludger, 2018. "Can Online Surveys Represent the Entire Population?," IZA Discussion Papers 11799, Institute of Labor Economics (IZA).
    5. Guido W. Imbens, 2015. "Matching Methods in Practice: Three Examples," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 373-419.
    6. Matthias Schonlau & Arthur van Soest & Arie Kapteyn & Mick Couper, 2009. "Selection Bias in Web Surveys and the Use of Propensity Scores," Sociological Methods & Research, , vol. 37(3), pages 291-318, February.
    7. Falbe, J. & Thompson, H.R. & Becker, C.M. & Rojas, N. & McCulloch, C.E. & Madsen, K.A., 2016. "Impact of the Berkeley excise tax on sugar-sweetened beverage consumption," American Journal of Public Health, American Public Health Association, vol. 106(10), pages 1865-1871.
    8. 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.
    9. Schlapfer, Felix & Roschewitz, Anna & Hanley, Nick, 2004. "Validation of stated preferences for public goods: a comparison of contingent valuation survey response and voting behaviour," Ecological Economics, Elsevier, vol. 51(1-2), pages 1-16, November.
    10. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sara Fernández Sánchez-Escalonilla & Carlos Fernández-Escobar & Miguel Ángel Royo-Bordonada, 2022. "Public Support for the Imposition of a Tax on Sugar-Sweetened Beverages and the Determinants of Such Support in Spain," IJERPH, MDPI, vol. 19(7), pages 1-12, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rahul Singh & Liyuan Xu & Arthur Gretton, 2020. "Kernel Methods for Causal Functions: Dose, Heterogeneous, and Incremental Response Curves," Papers 2010.04855, arXiv.org, revised Oct 2022.
    2. Susan Athey & Guido W. Imbens, 2017. "The State of Applied Econometrics: Causality and Policy Evaluation," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 3-32, Spring.
    3. Ainembabazi, John Herbert & Abdoulaye, Tahirou & Feleke, Shiferaw & Alene, Arega & Dontsop-Nguezet, Paul M. & Ndayisaba, Pierre Celestin & Hicintuka, Cyrille & Mapatano, Sylvain & Manyong, Victor, 2018. "Who benefits from which agricultural research-for-development technologies? Evidence from farm household poverty analysis in Central Africa," World Development, Elsevier, vol. 108(C), pages 28-46.
    4. Kebebe, E. & Shibru, F., 2017. "Impact of alternative livelihood interventions on household welfare: Evidence from rural Ethiopia," Forest Policy and Economics, Elsevier, vol. 75(C), pages 67-72.
    5. Nicolas Moreau, 2018. "A SAS macro to estimate Average Treatment Effects with Propensity Score Matching," Working Papers hal-01691528, HAL.
    6. Shen, Chung-Hua & Wu, Meng-Wen & Chen, Ting-Hsuan & Fang, Hao, 2016. "To engage or not to engage in corporate social responsibility: Empirical evidence from global banking sector," Economic Modelling, Elsevier, vol. 55(C), pages 207-225.
    7. Carlos A. Flores & Oscar A. Mitnik, 2009. "Evaluating Nonexperimental Estimators for Multiple Treatments: Evidence from Experimental Data," Working Papers 2010-10, University of Miami, Department of Economics.
    8. Difang Huang & Jiti Gao & Tatsushi Oka, 2022. "Semiparametric Single-Index Estimation for Average Treatment Effects," Papers 2206.08503, arXiv.org, revised Apr 2024.
    9. Sibhatu, Kibrom T. & Arslan, Aslihan & Zucchini, Emanuele, 2022. "The effect of agricultural programs on dietary diversity and food security: Insights from the smallholder productivity promotion program in Zambia," Food Policy, Elsevier, vol. 113(C).
    10. Zhaonan Qu & Ruoxuan Xiong & Jizhou Liu & Guido Imbens, 2021. "Semiparametric Estimation of Treatment Effects in Observational Studies with Heterogeneous Partial Interference," Papers 2107.12420, arXiv.org, revised Jun 2024.
    11. Farrell, Max H., 2015. "Robust inference on average treatment effects with possibly more covariates than observations," Journal of Econometrics, Elsevier, vol. 189(1), pages 1-23.
    12. Roberto ESPOSTI, 2014. "To match, not to match, how to match: Estimating the farm-level impact of the CAP-first pillar reform (or: How to Apply Treatment-Effect Econometrics when the Real World is;a Mess)," Working Papers 403, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    13. Seonho Shin, 2022. "Evaluating the Effect of the Matching Grant Program for Refugees: An Observational Study Using Matching, Weighting, and the Mantel-Haenszel Test," Journal of Labor Research, Springer, vol. 43(1), pages 103-133, March.
    14. Alejo, Javier & Galvao, Antonio F. & Montes-Rojas, Gabriel, 2018. "Quantile continuous treatment effects," Econometrics and Statistics, Elsevier, vol. 8(C), pages 13-36.
    15. Gao, Yanyan & Zheng, Jianghuai, 2020. "The impact of high-speed rail on innovation: An empirical test of the companion innovation hypothesis of transportation improvement with China’s manufacturing firms," World Development, Elsevier, vol. 127(C).
    16. Lee, Ying-Ying, 2018. "Efficient propensity score regression estimators of multivalued treatment effects for the treated," Journal of Econometrics, Elsevier, vol. 204(2), pages 207-222.
    17. Esposti, Roberto, 2014. "The Impact of the 2005 CAP-First Pillar Reform as a Multivalued Treatment Effect -Alternative Estimation Approaches," 2014 Third Congress, June 25-27, 2014, Alghero, Italy 173005, Italian Association of Agricultural and Applied Economics (AIEAA).
    18. Lars Thiel, 2015. "Leave the Drama on the Stage: The Effect of Cultural Participation on Health," SOEPpapers on Multidisciplinary Panel Data Research 767, DIW Berlin, The German Socio-Economic Panel (SOEP).
    19. Himaz, Rozana, 2020. "Sweet are the fruit of adversity? The impact of fathers’ death on child non-cognitive outcomes in Ethiopia," Economics & Human Biology, Elsevier, vol. 38(C).
    20. Aragón, Fernando M., 2015. "Do better property rights improve local income?: Evidence from First Nations' treaties," Journal of Development Economics, Elsevier, vol. 116(C), pages 43-56.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ehbiol:v:38:y:2020:i:c:s1570677x1930276x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/622964 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.