Policymakers routinely make high-stakes funding decisions. Assessing the value of a
program is difficult and may be affected by bounded rationality. We conducted experiments …

The drift diffusion model (DDM) is a prominent account of how people make decisions. Many
of these decisions involve comparing two alternatives based on differences of perceived …

Behavioral science demands skillful experimentation and high-quality data that are typically
gathered in person. However, the COVID-19 pandemic forced many behavioral research …

Decisions take time, and the time taken to reach a decision is likely to be informative about
the cost of more precise judgments. We formalize this insight using a dynamic model of …

The drift-diffusion model (DDM) is a model of sequential sampling with diffusion signals,
where the decision maker accumulates evidence until the process hits either an upper or …

Abstract Across five experiments (N= 1,714), we test whether people engage in wishful
thinking to alleviate anxiety about adverse future outcomes. Participants perform pattern …

We conducted an experiment causally manipulating reliance on more intuitive vs. more
deliberative behavior through time pressure and time delay. Our design uses a novel …

In this paper, we provide an axiomatic foundation for the value-based version of the drift
diffusion model (DDM) of Ratcliff, a successful model that describes two-alternative speeded …

Structural methods to estimate preferences for decisions under risk often perform poorly
when predicting new decisions out of sample. We compare standard structural methods to a …

Without strong assumptions about how noise manifests in choices, we can infer little from
existing empirical observations of the common ratio effect (CRE) about whether there exists …