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Who Participates in Household Scanning Panels?

Author

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  • Jayson L. Lusk
  • Kathleen Brooks

Abstract

We compare two widely used household scanning panels maintained by the Nielsen Company and Information Resources Inc. to a random sample of the U.S. population. Results indicate that the demographic characteristics of the random sample more closely match the Census Bureau data than the household scanning panels. We also show that after controlling for demographic differences, participants in the household scanning panels are slightly more price sensitive than participants in the random sample. The two household scanning panels yield similar results in relation to one another, which suggests that the household scanning panels may suffer from sample selection and participation biases. Copyright 2010, Oxford University Press.

Suggested Citation

  • Jayson L. Lusk & Kathleen Brooks, 2010. "Who Participates in Household Scanning Panels?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(1), pages 226-240.
    • Handle: RePEc:oup:ajagec:v:93:y:2010:i:1:p:226-240
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    File URL: http://hdl.handle.net/10.1093/ajae/aaq123
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    Cited by:

    1. Richard Friberg & Mark Sanctuary, 2018. "Market stealing and market expansion: an examination of product introductions in the organic coffee market," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 20(2), pages 287-303, April.
    2. Chen Zhen & Mary Muth & Abigail Okrent & Shawn Karns & Derick Brown & Peter Siegel, 2019. "Do differences in reported expenditures between household scanner data and expenditure surveys matter in health policy research?," Health Economics, John Wiley & Sons, Ltd., vol. 28(6), pages 782-800, June.
    3. Christoph, Inken B. & Buergelt, Doreen & Salamon, Petra & Weible, Daniela & Zander, Katrin, 2012. "A Holistic Approach to Consumer Research on Expectations Regarding Animal Husbandry," 2012 International European Forum, February 13-17, 2012, Innsbruck-Igls, Austria 144963, International European Forum on System Dynamics and Innovation in Food Networks.
    4. Daniele Asioli & Adriana Mignani & Frode Alfnes, 2021. "Quick and easy? Respondent evaluations of the Becker–DeGroot–Marschak and multiple price list valuation mechanisms," Agribusiness, John Wiley & Sons, Ltd., vol. 37(2), pages 215-234, April.
    5. Schroeter, Christiane & Cai, Xiaowei, 2011. "It’s All About Produce: Flexing the Muscles of Western U.S. Organic Spinach Consumption," Western Economics Forum, Western Agricultural Economics Association, vol. 10(2), pages 1-13.
    6. Rachel Griffith & Martin O'Connell & Kate Smith, 2017. "The Importance of Product Reformulation Versus Consumer Choice in Improving Diet Quality," Economica, London School of Economics and Political Science, vol. 84(333), pages 34-53, January.
    7. Andrew Leicester, 2012. "How might in-home scanner technology be used in budget surveys?," IFS Working Papers W12/01, Institute for Fiscal Studies.
    8. T. Bruce Lauber & Nancy A. Connelly & Jeff Niederdeppe & Barbara A. Knuth, 2018. "Effects of an Advisory Brochure on Fish Consumption of Urban Anglers in the Great Lakes Region," Risk Analysis, John Wiley & Sons, vol. 38(7), pages 1405-1421, July.
    9. Zhen, Chen & Muth, Mary K. & Karns, Shawn & Brown, Derick & Siegel, Peter, 2015. "Do Differences in Reported Expenditures between Commercial Household-based Scanner Data and Government Surveys Matter in a Structural Model of Food Demand?," 143rd Joint EAAE/AAEA Seminar, March 25-27, 2015, Naples, Italy 202702, European Association of Agricultural Economists.
    10. Brenna Ellison & Kathleen Brooks & Taro Mieno, 2017. "Which livestock production claims matter most to consumers?," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 34(4), pages 819-831, December.
    11. Schroeter, Christiane & Cai, Xiaowei, 2012. "The Impact of Food Environment on Branded vs. Private Label Produce Choice," 2012 AAEA/EAAE Food Environment Symposium 123197, Agricultural and Applied Economics Association.
    12. Nancy A. Connelly & T. Bruce Lauber & Jeff Niederdeppe & Barbara A. Knuth, 2018. "Using a Web‐Based Diary Method to Estimate Risks and Benefits from Fish Consumption," Risk Analysis, John Wiley & Sons, vol. 38(6), pages 1116-1127, June.
    13. Schroeter Christiane & Cai Xiaowei, 2012. "The Impact of Food Environment on Private Label versus Branded Produce Choice," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 10(1), pages 1-23, November.

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