New Economics Papers
on Neuroeconomics
Issue of 2011‒03‒26
two papers chosen by

  1. Hormones and Social Preferences By Thomas Buser
  2. Probability Matching and Reinforcement Learning* By Javier Rivas

  1. By: Thomas Buser (University of Amsterdam)
    Abstract: We examine whether social preferences are determined by hormones. We do this by investigating whether markers for the strength of prenatal testosterone exposure (finger length ratios) and current exposure to progesterone and oxytocin (the menstrual cycle) are correlated with choices in social preference games. We find that subjects with finger ratios indicating high prenatal testosterone exposure give less in the trust, ultimatum and public good games and return a smaller proportion in the trust game. The choices of female subjects vary over the menstrual cycle according to a pattern consistent with a positive impact of oxytocin on giving in the trust and ultimatum games and a positive impact of progesterone on altruism. We find no impact for subjects taking hormonal contraceptives. We conclude that both prenatal and current exposure to hormones play an important role in shaping social preferences.
    Keywords: social preferences; 2D:4D; testosterone; progesterone; oxytocin
    JEL: C91 D87
    Date: 2011–02–24
  2. By: Javier Rivas
    Abstract: Probability matching occurs when an action is chosen with a frequency equivalent to the probability of that action being the best choice. This sub-optimal behavior has been reported repeatedly by psychologist and experimental economist. We provide an evolutionary foundation for this phenomenon by showing that learning by reinforcement can lead to probability matching and, if learning occurs suffciently slowly, probability matching does not only occur in choice frequencies but also in choice probabilities. Our results are completed by proving that there exists no quasi-linear reinforcement learning specification such that behavior is optimal for all environments where counterfactuals are observed.
    Keywords: Probability Matching; Reinforcement Learning
    JEL: C73
    Date: 2011–03

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