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Do On-lookers See Most of the Game? Evaluating Job-seekers' Competitiveness of Oneself versus of Others in a Labor Market Experiment

Author

Listed:
  • Hu Sun

    (University of Michigan)

  • Yun Wang

    (Xiamen University)

Abstract

Competing in the labor market requires job-seekers to evaluate the competitiveness of themselves and of others. Will their evaluations of others be more objective and their evaluations of themselves be more biased? Will successful and unsuccessful job-seekers in the same labor market engage in different patterns while making their evaluations? We design a laboratory experiment to study the dynamics of job-seeking strategies and individuals' belief updating in a labor market. Our experimental treatments feature the decision-making and the evaluation of competitiveness of oneself versus of others. The probability of being accepted for a job depends on external shocks as well as the individuals' ability ranking. We find that subjects are less likely to evaluate others' competitiveness as high as their own in the same situation. Subjects are more inclined to attribute failure to external shocks and attribute success to their own competitiveness. Estimation results from a reinforcement learning model show that, compared to decision-making for others, subjects have a higher tolerance for failure and remain in applying for unsuitable jobs for longer periods when seeking jobs for themselves. Our findings provide evidence for the presence of self-serving attributional bias when individuals' self-image affects their economic decisions.

Suggested Citation

  • Hu Sun & Yun Wang, 2019. "Do On-lookers See Most of the Game? Evaluating Job-seekers' Competitiveness of Oneself versus of Others in a Labor Market Experiment," Working Papers 2019-07-11, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    • Handle: RePEc:wyi:wpaper:002515
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    More about this item

    Keywords

    Decision-making for others; Labor market experiment; Belief updating; Belief elicitation; Reinforcement learning; Self-serving attribution bias;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

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