We design an experiment to study investment behavior in different repeated contest settings, varying the uncertainty of the outcomes and the number of participants in contests. We find decreasing over-expenditures and a higher rate of ‘dropout’ in contests with high uncertainty over outcomes (winner-take-all contests), while we detect a quick convergence toward equilibrium predictions and a near to full participation when this type of uncertainty vanishes (proportional-prize contests). These results are robust to changes in the number of contestants. A learning parameter estimation using the experience-weighted attraction (EWA) model suggests that subjects adopt different learning modes across different contest structures and helps to explain expenditure patterns deviating from theoretical predictions.

Learning and dropout in contests: an experimental approach

Niederreiter J.;Riccaboni M.
2020-01-01

Abstract

We design an experiment to study investment behavior in different repeated contest settings, varying the uncertainty of the outcomes and the number of participants in contests. We find decreasing over-expenditures and a higher rate of ‘dropout’ in contests with high uncertainty over outcomes (winner-take-all contests), while we detect a quick convergence toward equilibrium predictions and a near to full participation when this type of uncertainty vanishes (proportional-prize contests). These results are robust to changes in the number of contestants. A learning parameter estimation using the experience-weighted attraction (EWA) model suggests that subjects adopt different learning modes across different contest structures and helps to explain expenditure patterns deviating from theoretical predictions.
2020
Contest
Dropout
Experience-weighted attraction
Experiment
Learning
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11771/17179
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