The favorite-longshot bias describes the longstanding empirical regularity that betting odds provide biased estimates of the probability of a horse winning – longshots are overbet, while favorites are underbet. Neoclassical explanations of this phenomenon focus on rational gamblers who overbet...

We introduce DOSE - Dynamically Optimized Sequential Experimentation - and use it to estimate individual-level loss aversion in a representative sample of the U.S. population (N = 2;000). DOSE elicitations are more accurate, more stable across time, and faster to administer than standard methods....

We introduce DOSE - Dynamically Optimized Sequential Experimentation - to elicit preference parameters. DOSE starts with a model of preferences and a prior over the parameters of that model, then dynamically chooses a customized question sequence for each participant according to an...

The favorite-longshot bias describes the longstanding empirical regularity that betting odds provide biased estimates of the probability of a horse winning - longshots are overbet, while favorites are underbet. Neoclassical explanations of this phenomenon focus on rational gamblers who overbet...

The favorite-longshot bias describes the longstanding empirical regularity that betting odds provide biased estimates of the probability of a horse winning - longshots are overbet, while favorites are underbet. Neoclassical explanations of this phenomenon focus on rational gamblers who overbet...