On the Source and Instability of Probability Weighting
We propose and experimentally test a new theory of probability distortions in risky choice. The theory is based on a core principle from neuroscience called efficient coding, which states that information is encoded more accurately for those stimuli that the agent expects to encounter more frequently. As the agent's prior beliefs vary, the model predicts that probability distortions change systematically. We provide novel experimental evidence consistent with the prediction: lottery valuations are more sensitive to probabilities that occur more frequently under the subject's prior beliefs. Our theory generates additional novel predictions regarding heterogeneity and time variation in probability distortions.
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