Deferred Acceptance (DA), a widely implemented algorithm, is meant to improve allocations: under classical preferences, it induces preference-concordant rankings. However, recent evidence shows that—in both real, large-stakes applications and experiments—participants frequently play...

How do people compare bundles of social-distancing behaviors? During the COVID pandemic, we showed 676 online respondents in the US, UK, and Israel 30 pairs of brief videos of acquaintances meeting. We asked them to indicate which in each pair depicted greater risk of COVID infection. Their...

This paper describes results of a pair of incentivized experiments on biases in judgments about random samples. Consistent with the Law of Small Numbers (LSN), participants exaggerated the likelihood that short sequences and random subsets of coin flips would be balanced between heads and tails....

We present a model of a financial market where some traders are "cursed" when choosing how much to invest in a risky asset, failing to fully take into account what prices convey about others' private information. Cursed traders put more weight on their private signals than rational traders. But...

Group testing increases efficiency by pooling patient specimens and clearing the entire group with one negative test. Optimal grouping strategy is well studied in one-off testing scenarios with reasonably well-known prevalence rates and no correlations in risk. We discuss how the strategy...

We model religious faith as a "demand for beliefs," following the logic of the Pascalian wager. We then demonstrate how an experimental intervention can exploit standard elicitation techniques to measure religious belief by varying prizes associated with making choices contrary to one's belief...

Experimental tests of dynamically inconsistent time preferences have largely relied on choices over time-dated monetary rewards. Several recent studies have failed to find the standard patterns of time inconsistency. However, such monetary studies contain often discussed confounds. In this...

Group testing increases efficiency by pooling patient specimens and clearing the entire group with one negative test. Optimal grouping strategy is well studied in one-off testing scenarios with reasonably well-known prevalence rates and no correlations in risk. We discuss how the strategy...