The Rationality of Decision Biases
12 Pages Posted: 3 Jan 2018 Last revised: 31 Jul 2018
Date Written: June 30, 2018
Biases may lead to smaller variability, which raises the decision-maker's expected concave utility. As a result, seeking unbiased estimators can be a strictly dominated decision approach. Moreover, by aggregating unrelated tasks and leveraging supposedly irrelevant information, the decision-maker may improve the unbiased decision by shrinking it toward an arbitrarily chosen reference point. This revelation highlights the difference between probability theory and statistical inference. Moreover, it leads to novel testable hypotheses for estimation problems when the knowledge is primarily gained through experience and observation. Built upon the findings of anchoring effects in behavioral economics, we further illustrate that compared to economic models based on probability theory, economic models based on statistical inference better reconcile the gap between rational theories and descriptive behavior.
Keywords: Decision Making under Uncertainty, Behavioral Economics, Decision Theory, James-Stein Shrinkage, Anchoring
JEL Classification: B20, C10, C11, D01, D81
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