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A simple diagnostic measure of inattention bias in discrete choice models

Author

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  • Trey Malone
  • Jayson L Lusk

Abstract

This note introduces a simple, easy-to-understand measure of inattention bias in discrete choice models. The metric, ranging from 0 to 1, can be compared across studies and samples. Specifically, a latent class logit model is estimated with all parameters in one class restricted to zero. The estimated share of observations falling in the class with null parameters (representing random choices) is the diagnostic measure of interest – the random response share. We validate the metric with an empirical study that identifies inattentive respondents via a trap question.

Suggested Citation

  • Trey Malone & Jayson L Lusk, 2018. "A simple diagnostic measure of inattention bias in discrete choice models," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 45(3), pages 455-462.
    • Handle: RePEc:oup:erevae:v:45:y:2018:i:3:p:455-462.
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    File URL: http://hdl.handle.net/10.1093/erae/jby005
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    Citations

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    Cited by:

    1. Trey Malone & Jayson L. Lusk, 2019. "Releasing The Trap: A Method To Reduce Inattention Bias In Survey Data With Application To U.S. Beer Taxes," Economic Inquiry, Western Economic Association International, vol. 57(1), pages 584-599, January.
    2. Tanga Mohr & John C. Whitehead, 2023. "External Validity of Inferred Attribute NonAttendance: Evidence from a Laboratory Experiment with Real and Hypothetical Payoffs," Working Papers 23-05, Department of Economics, Appalachian State University.
    3. Lusk, Jayson L. & Tonsor, Glynn T. & Schroeder, Ted C. & Hayes, Dermot J., 2018. "Effect of government quality grade labels on consumer demand for pork chops in the short and long run," Food Policy, Elsevier, vol. 77(C), pages 91-102.
    4. Lagerkvist, C.J. & Edenbrandt, A.K. & Tibbelin, I. & Wahlstedt, Y., 2020. "Preferences for sustainable and responsible equity funds - A choice experiment with Swedish private investors," Journal of Behavioral and Experimental Finance, Elsevier, vol. 28(C).
    5. 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.
    6. Andersson, Henrik & Ouvrard, Benjamin, 2023. "Priming and the value of a statistical life: A cross country comparison," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 104(C).
    7. Andersson, Henrik & Ouvrard, Benjamin, 2023. "Priming and the Value of a Statistical Life: A Cross Country Comparison," TSE Working Papers 23-1439, Toulouse School of Economics (TSE).
    8. Aaron Staples & Bridget K. Behe & Patricia Huddleston & Trey Malone, 2022. "What you see is what you get, and what you don't goes unsold: Choice overload and purchasing heuristics in a horticulture lab experiment," Agribusiness, John Wiley & Sons, Ltd., vol. 38(3), pages 620-635, July.

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