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Does Eye-Tracking Have an Effect on Economic Behavior?

Author

Listed:
  • Jennifer Kee
  • Melinda Knuth
  • Joanna Lahey
  • Marco A. Palma

Abstract

Eye-tracking is becoming an increasingly popular tool for understanding the underlying behavior driving economic decisions. However, an important unanswered methodological question is whether the use of an eye-tracking device itself induces changes in the behavior of experiment participants. We study this question using eight popular games in experimental economics. We implement a simple design where participants are randomly assigned to either a control or an eye-tracking treatment condition. In seven of the eight games, eye-tracking did not produce different outcomes. In the Holt and Laury risk assessment (HL), subjects with multiple calibration attempts behave like outliers under eye-tracking conditions, skewing the overall results. Further exploration shows that poor calibrators also show marginally higher levels of negative emotion, which is correlated with higher risk aversion in both HL and in the Eckel and Grossman gambling tasks. Because difficulty calibrating is correlated with eye-tracking data quality, the standard practice of removing participants who did not have good eye-tracking data quality resulted in no difference between the treatment and control groups in HL. Our results suggest that experiments may incorporate eye-tracking equipment without inducing changes in the economic behavior of participants, particularly after observations with low eye-tracking quality are removed.

Suggested Citation

  • Jennifer Kee & Melinda Knuth & Joanna Lahey & Marco A. Palma, 2020. "Does Eye-Tracking Have an Effect on Economic Behavior?," NBER Working Papers 28223, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:28223
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    2. Michelle S. Segovia & Marco A. Palma & Jayson L. Lusk & Andreas C. Drichoutis, 2025. "Visual formats in risk preference elicitation: What catches the eye?," Journal of Risk and Uncertainty, Springer, vol. 70(3), pages 275-303, June.
    3. Kashirina, A., 2024. "Factors influencing the choice of savings and investment instruments by generation Z: The experimental study using neuroequipment," Journal of the New Economic Association, New Economic Association, vol. 63(2), pages 144-167.
    4. Bigné, Enrique & Ruiz-Mafé, Carla & Badenes-Rocha, Alberto, 2023. "The influence of negative emotions on brand trust and intention to share cause-related posts: A neuroscientific study," Journal of Business Research, Elsevier, vol. 157(C).
    5. Fischbacher, Urs & Hausfeld, Jan & Renerte, Baiba, 2022. "Strategic incentives undermine gaze as a signal of prosocial motives," Games and Economic Behavior, Elsevier, vol. 136(C), pages 63-91.
    6. Gorny, Paul M. & Groos, Eva & Strobel, Christina, 2024. "Do Personalized AI Predictions Change Subsequent Decision-Outcomes? The Impact of Human Oversight," MPRA Paper 121065, University Library of Munich, Germany.
    7. Kiryluk-Dryjska, Ewa & Rani, Anshu, 2023. "Neuroeconomic Studies in Agriculture and Food Economics: A Systematic Review of Literature," Roczniki (Annals), Polish Association of Agricultural Economists and Agribusiness - Stowarzyszenie Ekonomistow Rolnictwa e Agrobiznesu (SERiA), vol. 2023(4).

    More about this item

    JEL classification:

    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty

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