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Experienced vs. inexperienced participants in the lab: do they behave differently?

Author

Listed:
  • Volker Benndorf

    (Goethe University Frankfurt)

  • Claudia Moellers

    (Heinrich Heine University Düsseldorf)

  • Hans-Theo Normann

    (Heinrich Heine University Düsseldorf)

Abstract

We analyze whether subjects with extensive laboratory experience and first-time participants, who voluntarily registered for the experiment, differ in their behavior. Subjects play four one-shot, two-player games: a trust game, a beauty contest, an ultimatum game, a traveler’s dilemma and, in addition, we conduct a single-player lying task and elicit risk preferences. We find few significant differences. In the trust game, experienced subjects are less trustworthy and they also trust less. Furthermore, experienced subjects submit fewer non-monotonic strategies in the risk elicitation task. We find no differences whatsoever in the other decisions. Nevertheless, the minor differences observed between experienced and inexperienced subjects may be relevant because we document a potential recruitment bias: the share of inexperienced subjects may be lower in the early recruitment waves.

Suggested Citation

  • Volker Benndorf & Claudia Moellers & Hans-Theo Normann, 2017. "Experienced vs. inexperienced participants in the lab: do they behave differently?," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 3(1), pages 12-25, July.
  • Handle: RePEc:spr:jesaex:v:3:y:2017:i:1:d:10.1007_s40881-017-0036-z
    DOI: 10.1007/s40881-017-0036-z
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    3. Ellen Garbarino & Robert Slonim & Marie Claire Villeval, 2018. "A method to estimate mean lying rates and their full distribution," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 4(2), pages 136-150, December.
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    5. Jonathan Schulz & Uwe Sunde & Petra Thiemann & Christian Thoeni, 2019. "Selection into Experiments: Evidence from a Population of Students," Discussion Papers 2019-09, The Centre for Decision Research and Experimental Economics, School of Economics, University of Nottingham.
    6. Schmidt, Robert & Schwieren, Christiane & Sproten, Alec N., 2020. "Norms in the lab: Inexperienced versus experienced participants," Journal of Economic Behavior & Organization, Elsevier, vol. 173(C), pages 239-255.
    7. Tiziana Medda & Vittorio Pelligra & Tommaso Reggiani, 2021. "Lab-Sophistication: Does Repeated Participation in Laboratory Experiments Affect Pro-Social Behaviour?," Games, MDPI, vol. 12(1), pages 1-14, February.
    8. Thiemann, Petra & Schulz, Jonathan & Sunde, Uwe & Thöni, Christian, 2022. "Selection into experiments: New evidence on the role of preferences, cognition, and recruitment protocols," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 98(C).
    9. Shaun P. Hargreaves Heap & Eugenio Levi & Abhijit Ramalingam, 2021. "Group identification and giving: in-group love, out-group hate and their crowding out," MUNI ECON Working Papers 2021-07, Masaryk University, revised Feb 2023.
    10. Roggenkamp, Hauke C., 2024. "Revisiting ‘Growth and Inequality in Public Good Provision’—Reproducing and Generalizing Through Inconvenient Online Experimentation," OSF Preprints 6rn97, Center for Open Science.
    11. Chapkovski, Philipp, 2023. "Conducting interactive experiments on Toloka," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    12. Ellen Garbarino & Robert Slonim & Marie Claire Villeval, 2018. "A Method to Estimate Mean Lying Rates and Their Full Distribution," Post-Print halshs-01896598, HAL.
    13. Kleinlercher, Daniel & Stöckl, Thomas, 2021. "Thou shalt not trade—An analysis of the violations of no-trade predictions in experimental asset markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
    14. Müller, Stephan & Rau, Holger A., 2020. "Motivational crowding out effects in charitable giving: Experimental evidence," Journal of Economic Psychology, Elsevier, vol. 76(C).
    15. Dengler-Roscher, Kathrin & Montinari, Natalia & Panganiban, Marian & Ploner, Matteo & Werner, Benedikt, 2018. "On the malleability of fairness ideals: Spillover effects in partial and impartial allocation tasks," Journal of Economic Psychology, Elsevier, vol. 65(C), pages 60-74.
    16. Laurent Denant-Boemont & Matthieu Leprince & Matthieu Pourieux, 2019. "Distributive Preferences of Public Representatives: A Field-in-the-Lab Experiment," Economics Working Paper from Condorcet Center for political Economy at CREM-CNRS 2019-05-ccr, Condorcet Center for political Economy.
    17. Fortuna Casoria & Fabio Galeotti & Marie Claire Villeval, 2023. "Trust and social preferences in times of acute health crisis," Working Papers 2304, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    18. Chapkovski, Philipp, 2022. "Interactive Experiments in Toloka," EconStor Preprints 249771, ZBW - Leibniz Information Centre for Economics.
    19. Schmidt, Robert J. & Schwieren, Christiane & Sproten, Alec N., 2018. "Social Norm Perception in Economic Laboratory Experiments: Inexperienced versus Experienced Participants," Working Papers 0656, University of Heidelberg, Department of Economics.
    20. Palan, Stefan & Schitter, Christian, 2018. "Prolific.ac—A subject pool for online experiments," Journal of Behavioral and Experimental Finance, Elsevier, vol. 17(C), pages 22-27.
    21. Benndorf, Volker & Rau, Holger A. & Sölch, Christian, 2019. "Minimizing learning in repeated real-effort tasks," Journal of Behavioral and Experimental Finance, Elsevier, vol. 22(C), pages 239-248.
    22. Aurélie Dariel & Nikos Nikiforakis & Jan Stoop, 2020. "Does selection bias cause us to overestimate gender differences in competitiveness?," Working Papers 20200046, New York University Abu Dhabi, Department of Social Science, revised May 2020.
    23. Chapkovski, Philipp, 2022. "Interactive experiments in Toloka," MPRA Paper 111980, University Library of Munich, Germany.

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    More about this item

    Keywords

    Dilemma; Experienced subjects; Laboratory methods; Trust game;
    All these keywords.

    JEL classification:

    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games

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