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Travelers' types

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  • Brañas-Garza, Pablo
  • Espinosa, María Paz
  • Rey-Biel, Pedro

Abstract

This paper uses subjects' diverse self-reported justifications to explain discrepancies between observed heterogeneous behavior and the unique equilibrium prediction in a one-shot traveler's dilemma experiment. Principal components analysis suggests that iterative reasoning, aspiration levels, competitive behavior, attitudes towards risk and penalties and focal points may be behind different choices. Such reasons are coherent with same subjects' behavior in other tests and experiments in which these particular issues are prominent, and thus, we identify "types" of subjects. Overall, we conclude that subjects' self-justifications in complex strategic situations contain informational value which may be used to predict behavior in other situations of economic importance.

Suggested Citation

  • Brañas-Garza, Pablo & Espinosa, María Paz & Rey-Biel, Pedro, 2011. "Travelers' types," Journal of Economic Behavior & Organization, Elsevier, vol. 78(1-2), pages 25-36, April.
    • Handle: RePEc:eee:jeborg:v:78:y:2011:i:1-2:p:25-36
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    Cited by:

    1. Morone, A. & Morone, P. & Germani, A.R., 2014. "Individual and group behaviour in the traveler's dilemma: An experimental study," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 49(C), pages 1-7.
    2. Andrea Morone & Piergiuseppe Morone, 2016. "The Focal Point In The Traveller'S Dilemma: An Experimental Study," Bulletin of Economic Research, Wiley Blackwell, vol. 68(S1), pages 123-132, December.
    3. Ispano, Alessandro & Schwardmann, Peter, 2017. "Cooperating over losses and competing over gains: A social dilemma experiment," Games and Economic Behavior, Elsevier, vol. 105(C), pages 329-348.
    4. Kiss, H.J. & Rodriguez-Lara, I. & Rosa-García, A., 2016. "Think twice before running! Bank runs and cognitive abilities," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 64(C), pages 12-19.
    5. Jones, Matthew T., 2014. "Strategic complexity and cooperation: An experimental study," Journal of Economic Behavior & Organization, Elsevier, vol. 106(C), pages 352-366.
    6. Sean Duffy & J. J. Naddeo & David Owens & John Smith, 2024. "Cognitive Load and Mixed Strategies: On Brains and Minimax," International Game Theory Review (IGTR), World Scientific Publishing Co. Pte. Ltd., vol. 26(03), pages 1-34, September.
    7. Al-Ubaydli, Omar & Jones, Garett & Weel, Jaap, 2016. "Average player traits as predictors of cooperation in a repeated prisoner's dilemma," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 64(C), pages 50-60.
    8. Juan M. Benito-Ostolaza & Penélope Hernández & Juan A. Sanchis-Llopis, 2015. "Are individuals with higher cognitive ability expected to play more strategically?," Working Papers 1507, Department of Applied Economics II, Universidad de Valencia.
    9. Benito-Ostolaza, Juan M. & Hernández, Penélope & Sanchis-Llopis, Juan A., 2016. "Do individuals with higher cognitive ability play more strategically?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 64(C), pages 5-11.
    10. Brañas-Garza, Pablo & García-Muñoz, Teresa & González, Roberto Hernán, 2012. "Cognitive effort in the Beauty Contest Game," Journal of Economic Behavior & Organization, Elsevier, vol. 83(2), pages 254-260.
    11. Rodrigo Moro & Esteban Freidin & Fernando Tohmé & Marcelo Auday, 2011. "La teoría de juegos conductual, el dilema del viajero alternativo y la maximización de pagos," Estudios de Economia, University of Chile, Department of Economics, vol. 38(2 Year 20), pages 457-473, December.
    12. Allred, Sarah & Duffy, Sean & Smith, John, 2016. "Cognitive load and strategic sophistication," Journal of Economic Behavior & Organization, Elsevier, vol. 125(C), pages 162-178.
    13. Bayer, Ralph C. & Renou, Ludovic, 2016. "Logical omniscience at the laboratory," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 64(C), pages 41-49.
    14. Duffy, Sean & Smith, John, 2014. "Cognitive load in the multi-player prisoner's dilemma game: Are there brains in games?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 51(C), pages 47-56.
    15. Baader, Malte & Vostroknutov, Alexander, 2017. "Interaction of reasoning ability and distributional preferences in a social dilemma," Journal of Economic Behavior & Organization, Elsevier, vol. 142(C), pages 79-91.
    16. Arad, Ayala & Rubinstein, Ariel, 2010. "The 11-20 Money Request Game: Evaluating the Upper Bound of k-Level Reasoning," Foerder Institute for Economic Research Working Papers 275738, Tel-Aviv University > Foerder Institute for Economic Research.
    17. Baghestanian, Sascha & Frey, Seth, 2016. "GO figure: Analytic and strategic skills are separable," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 64(C), pages 71-80.
    18. Chen, Chia-Ching & Chiu, I-Ming & Smith, John & Yamada, Tetsuji, 2013. "Too smart to be selfish? Measures of cognitive ability, social preferences, and consistency," Journal of Economic Behavior & Organization, Elsevier, vol. 90(C), pages 112-122.
    19. Gill, David & Prowse, Victoria, 2012. "Cognitive ability and learning to play equilibrium: A level-k analysis," MPRA Paper 38317, University Library of Munich, Germany, revised 23 Apr 2012.
    20. Rodrigo Moro & Esteban Freidin & Fernando Tohmé, 2015. "Social preferences are not enough: Accounting for anomalous behavior in a complex mixed-motive game," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, March.

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    More about this item

    Keywords

    Traveler's dilemma Self-reports Principal components Experiments;

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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