Investment under risk vs ambiguity

Last registered on April 26, 2024

Pre-Trial

Trial Information

General Information

Title
Investment under risk vs ambiguity
RCT ID
AEARCTR-0013437
Initial registration date
April 22, 2024

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
April 26, 2024, 12:02 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

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Primary Investigator

Affiliation

Other Primary Investigator(s)

PI Affiliation
UC Santa Barbara

Additional Trial Information

Status
In development
Start date
2024-04-24
End date
2024-06-14
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We compare investment decisions under risk (known probability of investment success) vs. ambiguity (unknown probability). We introduce ambiguity into the investment task developed by Gneezy and Potters (1997) and examine its impact on investment decisions, breaking it down into two components: a noisy prediction channel and an ambiguity attitudes channel.
External Link(s)

Registration Citation

Citation
Esponda, Ignacio and Leshan Xu. 2024. "Investment under risk vs ambiguity." AEA RCT Registry. April 26. https://doi.org/10.1257/rct.13437-1.0
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2024-04-24
Intervention End Date
2024-06-14

Primary Outcomes

Primary Outcomes (end points)
Investment decisions.
Guesses of the probability of success.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Each subject faces an individual decision problem over a span of several rounds. Each round presents two tasks: a guessing task and an investment task. In the guessing task, the subject is briefly shown a square grid containing one hundred dark grey and light grey balls of different sizes for one-tenth of a second. Their objective is to estimate the number of dark grey balls.

The investment task takes place after the guessing task. A single ball is randomly selected by the computer from the pool of one hundred balls, with the color undisclosed to the subject. The subject is endowed with an amount of money to invest and decides how much of that money to invest in a risky option. If the selected ball is dark grey, signifying success, the investment triples in return: the subject receives the uninvested amount plus three times the investment. Conversely, if the ball is light grey, indicating failure, the subject solely receives the uninvested amount.

After certain rounds, specifically with a one-third probability each round, the subject is prompted to report the distance between their guess and the actual number of dark grey balls. Accurate responses are required to advance to the subsequent round. The subject is informed that this measure is implemented to ensure sustained attention throughout the experiment.

We examine two treatments, differing solely in the timing of when the actual number of dark grey balls in a round is revealed. In fact, the instructions are identical for both treatments, except for one sentence detailing the timing of this revelation.

Risky treatment: The computer reveals the number of dark grey balls after the guessing task and before the investment task.
Ambiguous treatment: The computer reveals the number of dark grey balls at the end of the round (after the investment task).

Each subject is exposed to both treatments as follows. At the beginning of the experiment, each subject is randomized to the risky or ambiguous treatment. In the first part of the experiment, each subject does the treatment assigned to them. In the second part of the experiment, each subject does the other treatment.

In summary, there will be two treatments: (1) Risky first, ambiguity second, and (2) Ambiguity first, risky second.
Experimental Design Details
Not available
Randomization Method
Randomization is done by a computer.
Randomization Unit
Randomization is done at the individual subject level.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
We aim to recruit 140 subjects.
Sample size: planned number of observations
We aim to recruit 140 subjects.
Sample size (or number of clusters) by treatment arms
The 140 subjects will be randomized into one of two treatment arms.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
Institute for Social, Behavioral and Economic Research, UC Santa Barbara
IRB Approval Date
2023-09-20
IRB Approval Number
3-23-0555