We study the pattern of correlations across a large number of behavioral regularities, with the goal of creating an empirical basis for more comprehensive theories of decision-making. We elicit 21 behaviors using an incentivized survey on a representative sample (n = 1;000) of the U.S....

Willingness to pay (WTP) and willingness to accept (WTA) a monetary amount for a lottery should be closely related. In data from an incentivized survey of a representative sample of 3,000 U.S. adults, we find that WTA and WTP for a lottery are, at best, weakly correlated. Across all respondents,...

An enormous literature documents that willingness to pay (WTP) is less than willingness to accept (WTA) a monetary amount for an object, a phenomenon called the endowment effect. Using data from an incentivized survey of a representative sample of 3,000 U.S. adults, we add one (probably)...

In this paper, we introduce a new measure of how close a set of choices are to satisfying the observable implications of rational choice, and apply it to a large balanced panel of household level consumption data. We use this method to answer three related questions: (i) "How close are...

We study how healthcare subsidies and improved information affect over- and under-use of primary healthcare in a randomized control trial of 1544 children in Mali. In a dynamic model of healthcare demand, misuse relative to policymaker preferences (here given by WHO care-seeking standards)...

In this paper, we introduce a new measure of how close a set of choices are to satisfying the observable implications of rational choice, and apply it to a large balanced panel of household level consumption data. We use this method to answer three related questions: (i) 'How close are...

We use four incentivized representative surveys to study the endowment effect for lotteries in 4,000 U.S. adults. We replicate the standard finding of an endowment effect--the divergence between Willingness to Accept (WTA) and Willingness to Pay (WTP), but document three new findings. First, we...