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...

In experiments, people do not always appear to think very strategically or to infer the information of others from their choices. We report experimental results in games of private information with three information states, which vary in strategic complexity. “Mousetracking” is used to...

We measure individual-level loss aversion using three incentivized, representative surveys of the U.S. population (combined N = 3,000). We find that around 50% of the U.S. population is loss tolerant, with many participants accepting negative-expected-value gambles. This is counter to earlier...

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 - 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 measure individual-level loss aversion using three incentivized, representative surveys of the U.S. population (combined N = 3,000). We find that around 50% of the U.S. population is loss tolerant, with many participants accepting negative-expected-value gambles. This is counter to earlier...