Behavioral Economics Commons^™

Modelling Biased Judgement With Weighted Updating, Jesse A. Zinn

Jesse A Zinn

The weighted updating model is a generalization of Bayesian updating that allows for biased beliefs by weighting the functions that constitute Bayes’ rule with real exponents. This paper shows that weighting a distribution affects the information entropy of the resulting distribution, suggesting that weighted updating can model biases in which individuals mistake the information content of data. The paper augments the base model in two ways, allowing it to account for additional biases. The first expansion involves discrimination between data. The second allows the weights to vary over time. The paper also presents a set of sufficient conditions for the …