for (and against) each putative bias, and I highlight when and how different biases may be related to each other. The …

bias leading to a large body of related empirical work, with recent innovations in settings where decision makers are … bias in decision making in such settings. Our results call into question recent conclusions about racial bias among bail … differences in underlying individual characteristics, or by biased decision makers. Becker (1957) proposed an outcome test for …

Outcome bias occurs when an evaluator considers ex-post outcomes when judging whether a choice was correct, ex-ante. We … formalize this cognitive bias in a simple model of distorted Bayesian updating. We then examine strategy changes made by …

relative to non-coethnics. The results run strongly against the common presumption of extensive ethnic bias among ordinary …

and show they behave well in realistic scenarios, correcting the large bias problem of the full sample estimator. We use … data from the National JTPA Study and the Tennessee STAR experiment to demonstrate the performance of alternative …

The favorite-longshot bias describes the longstanding empirical regularity that betting odds provide biased estimates … misperceptions of probability drive the favorite-longshot bias, as suggested by Prospect Theory …

This paper considers causal inference and sample selection bias in non-experimental settings in which: (i) few units in …-treatment characteristics. We propose the use of propensity score matching methods and implement them using data from the NSW experiment … and compare the estimates of the treatment effect obtained using our methods to the benchmark results from the experiment …

We conduct a randomized field experiment to quantify biases that affect consumers of addictive goods: present …-biased preferences, naïve beliefs regarding present bias, and projection-biased beliefs over future abstinence. These biases reflect … important theoretical and policy ramifications. Our experiment employs a new approach for remote monitoring to ensure truthful …

imprecise (and noisy) mental representation of the decision situation. In this model, risk aversion is predicted without any … need for a nonlinear utility-of-wealth function, and instead results from a sort of perceptual bias -- but one that … represents an optimal Bayesian decision, given the limitations of the mental representation of the situation. We propose a …