Privacy protection is among the key features to consider in the design of central bank digital currency (CBDC). Using a nationally representative sample of over 3,500 participants, we conduct a randomized online survey experiment to examine how the willingness to use CBDC as a means of payment varies with the degree of privacy protection and information provision on the privacy benefits of using CBDC. We find that both factors significantly increase participants’ willingness to use CBDC by up to 64% when purchasing privacy-sensitive products. Our findings provide useful insights regarding the design and the public’s adoption of CBDC.

Privacy protection is among the key features to consider in the design of central bank digital currency (CBDC). Using a nationally representative sample of over 3,500 participants, we conduct a randomized online survey experiment to examine how the willingness to use CBDC as a means of payment varies with the degree of privacy protection and information provision on the privacy benefits of using CBDC. We find that both factors significantly increase participants’ willingness to use CBDC by up to 64% when purchasing privacy-sensitive products. Our findings provide useful insights regarding the design and the public’s adoption of CBDC.

Revealed preference theory offers a criterion for decision-making quality: if decisions are high quality then there exists a utility function the choices maximize. We conduct a large-scale experiment to test for consistency with utility maximization. Consistency scores vary markedly within and across socioeconomic groups. In particular, consistency is strongly related to wealth: a standard deviation increase in consistency is associated with 15-19 percent more household wealth. This association is quantitatively robust to conditioning on correlates of unobserved constraints, preferences, and beliefs. Consistency with utility maximization under laboratory conditions thus captures decision-making ability that applies across domains and influences important real-world outcomes.

Revealed preference theory offers a criterion for decision-making quality: if decisions are high quality then there exists a utility function the choices maximize. We conduct a large-scale experiment to test for consistency with utility maximization. Consistency scores vary markedly within and across socioeconomic groups. In particular, consistency is strongly related to wealth: a standard deviation increase in consistency is associated with 15-19 percent more household wealth. This association is quantitatively robust to conditioning on correlates of unobserved constraints, preferences, and beliefs. Consistency with utility maximization under laboratory conditions thus captures decision-making ability that applies across domains and influences important real-world outcomes.

Revealed preference theory offers a criterion for decision-making quality: if decisions are high quality then there exists a utility function the choices maximize. We conduct a large-scale experiment to test for consistency with utility maximization. Consistency scores vary markedly within and across socioeconomic groups. In particular, consistency is strongly related to wealth: a standard deviation increase in consistency is associated with 15-19 percent more household wealth. This association is quantitatively robust to conditioning on correlates of unobserved constraints, preferences, and beliefs. Consistency with utility maximization under laboratory conditions thus captures decision-making ability that applies across domains and influences important real-world outcomes.

By using graphical representations of simple portfolio choice problems, we generate a very rich dataset to study behavior under uncertainty at the level of the individual subject. We test the data for consistency with the maximization hypothesis, and we estimate preferences using a two-parameter utility function based on Faruk Gul (1991). This specification provides a good interpretation of the data at the individual level and can account for the highly heterogeneous behaviors observed in the laboratory. The parameter estimates jointly describe attitudes toward risk and allow us to characterize the distribution of risk preferences in the population. (JEL D11, D14, D81, G11)

By using graphical representations of simple portfolio choice problems, we generate a very rich dataset to study behavior under uncertainty at the level of the individual subject. We test the data for consistency with the maximization hypothesis, and we estimate preferences using a two-parameter utility function based on Faruk Gul (1991). This specification provides a good interpretation of the data at the individual level and can account for the highly heterogeneous behaviors observed in the laboratory. The parameter estimates jointly describe attitudes toward risk and allow us to characterize the distribution of risk preferences in the population. (JEL D11, D14, D81, G11)