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Consequences of Participant Inattention with an Application to Carbon Taxes for Meat Products

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  • Malone, Trey
  • Lusk, Jayson L.

Abstract

Despite widespread use in nonmarket valuation, data quality remains an ongoing challenge for survey methods. One key concern is whether participants attentively respond to survey questions or whether they exert less than full effort. To determine the prevalence and consequences of inattention bias in surveys, we estimate how meat demand varies across people who do and do not miss trap questions. Using a split-sample design with discrete choice experiments for meat products, we explore three different trap questions to determine how many potentially inattentive respondents are identified by each method. We find that individuals who miss trap questions respond differently to the choice experiment than individuals who correctly answer the trap question. Inattention generates vastly different compensating variation estimates of a carbon tax, ranging from 3.56 cents per meal choice for the least attentive to 6.13 cents per meal choice for the most attentive.

Suggested Citation

  • Malone, Trey & Lusk, Jayson L., 2018. "Consequences of Participant Inattention with an Application to Carbon Taxes for Meat Products," Ecological Economics, Elsevier, vol. 145(C), pages 218-230.
    • Handle: RePEc:eee:ecolec:v:145:y:2018:i:c:p:218-230
    DOI: 10.1016/j.ecolecon.2017.09.010
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    Citations

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    Cited by:

    1. Trey Malone & Antonios M. Koumpias & Per L. Bylund, 2019. "Entrepreneurial response to interstate regulatory competition: evidence from a behavioral discrete choice experiment," Journal of Regulatory Economics, Springer, vol. 55(2), pages 172-192, April.
    2. Vecchio, Riccardo & Caso, Gerarda & Cembalo, Luigi & Borrello, Massimiliano, 2020. "Is respondents’ inattention in online surveys a major issue for research?," Economia agro-alimentare / Food Economy, Italian Society of Agri-food Economics/Società Italiana di Economia Agro-Alimentare (SIEA), vol. 22(1), March.
    3. Chavez, Daniel E. & Palma, Marco A. & Nayga Jr., Rodolfo M., 2017. "When does real become consequential in non-hypothetical choice experiments?," 2018 Annual Meeting, February 2-6, 2018, Jacksonville, Florida 266327, Southern Agricultural Economics Association.
    4. Tavárez, Héctor & Elbakidze, Levan, 2019. "Valuing recreational enhancements in the San Patricio Urban Forest of Puerto Rico: A choice experiment approach," Forest Policy and Economics, Elsevier, vol. 109(C).
    5. Lew, Daniel K., 2018. "Discounting future payments in stated preference choice experiments," Resource and Energy Economics, Elsevier, vol. 54(C), pages 150-164.
    6. Haotian Cheng & Dayton M. Lambert & Karen L. DeLong & Kimberly L. Jensen, 2022. "Inattention, availability bias, and attribute premium estimation for a biobased product," Agricultural Economics, International Association of Agricultural Economists, vol. 53(2), pages 274-288, March.
    7. Brittney Goodrich & Marieke Fenton & Jerrod Penn & John Bovay & Travis Mountain, 2023. "Battling bots: Experiences and strategies to mitigate fraudulent responses in online surveys," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 45(2), pages 762-784, June.
    8. Jayson L Lusk, 2019. "Consumer beliefs about healthy foods and diets," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-15, October.
    9. Elliott J. Dennis & Glynn T. Tonsor & Jayson L. Lusk, 2021. "Choosing quantities impacts individuals choice, rationality, and willingness to pay estimates," Agricultural Economics, International Association of Agricultural Economists, vol. 52(6), pages 945-962, November.
    10. Erlend Dancke Sandorf, 2019. "Did You Miss Something? Inattentive Respondents in Discrete Choice Experiments," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 73(4), pages 1197-1235, August.
    11. Riccardo Vecchio & Gerarda Caso & Luigi Cembalo & Massimiliano Borrello, 2020. "Is respondents? inattention in online surveys a major issue for research?," Economia agro-alimentare, FrancoAngeli Editore, vol. 22(1), pages 1-18.
    12. Lusk, Jayson L., 2019. "Income and (Ir) rational food choice," Journal of Economic Behavior & Organization, Elsevier, vol. 166(C), pages 630-645.
    13. Héctor Tavárez & Alicia Barriga, 2023. "Economic Viability of Developing Passive Recreational Opportunities in Puerto Rico: Insights for Sustainable Forest Management," Sustainability, MDPI, vol. 15(21), pages 1-17, October.
    14. Bernard Korai & Rémy Lambert, 2023. "Les marques territoriales dans le secteur bioalimentaire : un outil pour favoriser l’achat local et de proximité," CIRANO Project Reports 2023rp-17, CIRANO.
    15. Erdem, Seda, 2018. "Who do UK consumers trust for information about nanotechnology?," Food Policy, Elsevier, vol. 77(C), pages 133-142.
    16. Hopkins, Kelsey A. & McKendree, Melissa G. S., 2020. "Do Ewe See what I See? Evidence of Conspicuous Consumption for Sustainably Labeled Wool Clothing," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304616, Agricultural and Applied Economics Association.

    More about this item

    Keywords

    Trap question; Inattention bias; Discrete choice experiment; Meat demand;
    All these keywords.

    JEL classification:

    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • Q18 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Policy; Food Policy; Animal Welfare Policy

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