Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This paper develops a new behavioral model of how experience affects willingness to trade called adaptive loss aversion. In the model, agents do not recognize that others have different information. Loss aversion makes them cautious. When trading, this protects them from being exploited by better-informed traders. The degree of loss aversion λ is adjusted in response to experience and carries over between games. When outcomes are better than anticipated, λ decreases; when outcomes are worse than anticipated, it increases. A repeated market experiment with symmetric and asymmetric information is used to test the model. The data are noisier than anticipated but some of the model’ s main predictions are supported. A structural version of the model is estimated using the experimental data and data from two previous experiments on the winner’s curse. A range of other behavioral game theory models is also estimated using the same data and the fit of the models is compared.