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Performance of a reciprocity model in predicting a positive reciprocity decision

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  • Bhirombhakdi, Kornpob
  • Potipiti, Tanapong

Abstract

This study experimentally tests the performance in predicting decisions of a reciprocity model that was proposed by Dufwenberg et al. (2004). By applying a new approach, the study directly and individually predicts a subject's future decision from his past decision. The prediction performance is measured by the rate of correct predictions (accuracy) and the gain in the rate of the correct predictions (informativeness). Six scenarios of trust game are used to test the model's performance. Further, we compare the performance of the model with two other prediction methods; one method uses a decision in a dictator game to predict a decision in a trust game; the other uses personal information including IQ-test scores, personal attitudes and socio-economic factors. Seventy-nine undergraduate students participated in this hand-run experimental study. The results show that the reciprocity model has the best performance when compared with other prediction methods.

Suggested Citation

  • Bhirombhakdi, Kornpob & Potipiti, Tanapong, 2012. "Performance of a reciprocity model in predicting a positive reciprocity decision," MPRA Paper 40954, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:40954
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    References listed on IDEAS

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    4. Bhirombhakdi, Kornpob, 2011. "Performance of a reciprocity model in predicting a positive reciprocity decision," MPRA Paper 37468, University Library of Munich, Germany.
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    Cited by:

    1. Bhirombhakdi, Kornpob, 2011. "Performance of a reciprocity model in predicting a positive reciprocity decision," MPRA Paper 37468, University Library of Munich, Germany.
    2. Bhirombhakdi, Kornpob & Potipiti, Tanapong, 2012. "Cost of action, perceived intention, positive reciprocity, and signalling model," MPRA Paper 37469, University Library of Munich, Germany.

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    More about this item

    Keywords

    Reciprocity; Model performance; Trust game;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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