Models derived from random utility theory represent the workhorse methods to learn about consumer preferences from discrete choice data. However, a large body of literature documents various behavioral patterns that cannot be captured by basic random utility models and require different...

We utilize a novel dataset that merges household administrative income and socio-demographic information from tax records with scanner data on CPG consumption. Our analysis reveals significant variation in household per-capita expenditures. However, we find only a modest economic relationship...

Artificial Intelligence has the potential to improve human decisions in complex environments, but its effectiveness can remain limited if humans hold context-specific private information. Using the empirical example of antibiotic prescribing for urinary tract infections, we show that full...