Decision-making under risk and uncertainty

2024-08-01

2026-06-30

The key outcome variable is the individual participant's decision about how much to invest in the investment games. Each participant will play a set of ten investment project games. Hence, one independent observation in a treatment will be a vector of ten investment choices by an individual participant, with each choice being between 0 and 8 dollars. We will then compare these decisions across three treatments.

To investigate the underlying behavioral mechanisms driving people towards innovative risky investment products, we will conduct controlled economic experiments in a laboratory. There will be three groups of participants, corresponding to three different treatments. We will test how investment decisions differ among these groups. Each participant will play a set of ten investment project games, which are identical across the three treatments; i.e., projects will have identical probabilities and identical payouts. Identical projects across the three groups will help control the factors that could otherwise influence investment decisions. The only difference among these treatments will be how the projects are presented.

For each project, participants will be given a virtual endowment of 8 dollars in the programmed experiment in Z-tree, from which they can allocate their stakes between 0 and 8 dollars for the investments. The difference between their endowment and the amount invested will be part of their profit from the investment. The other part will be the return on the investment, received only if it is successful.

In Treatment 1, projects will be presented as investment projects consisting of multiple sub-projects, without compound probability of success information. We will provide probability information for each sub-project to the participants but will not tell them the compound probability of success for all sub-projects in an investment project. However, participants will be provided with a profit calculator on the game screen, which will be optional to use. They may or may not use it to calculate the expected income from any investment value in case of both successful and unsuccessful outcomes. Using intuition, participants will decide on the optimal level of investment.

In Treatment 2, the same investment projects consisting of multiple sub-projects will be offered, but with compound probability information.

In Treatment 3, the same projects will be offered in the form of single investment projects. All three treatments will present the payout from each unit of investment stake explicitly. In our experiment, as the games are objective, the value of probability information given in the experiment is free from human judgment. Each participant will undergo only one of these three treatments, making this experiment a cross-subject design.

Not available

We randomly assign each experimental session to one of the 3 treatments. Participants voluntarily sign up to attend in our sessions. But at the time of registration, they do not know the treatment they will receive.

Session

Yes

As one independent observation will be a vector of ten investment choices by an individual participant, we will do clustering at individual level. The planned number of clusters is 150 and 10 observations per cluster. This approach captures the similarities in investment behavior across participants.

150 participants x 10 investment choices = 1,500 investment choices (observations)

Each treatment has 50 participants, and with three treatments, the total number of participants is 3 × 50 = 150.

The method of using 150 clusters will provide with a high degree of variance in investment behavior among participants, from risk-averse to risk loving. This plan for individual-level clustering with 150 clusters will give us more power for analyzing investment choices.