Peer effects and financial decision-making I

Last registered on September 17, 2021

Pre-Trial

Trial Information

General Information

Title
Peer effects and financial decision-making I
RCT ID
AEARCTR-0007896
Initial registration date
July 02, 2021
Last updated
September 17, 2021, 1:22 AM EDT

Locations

Region

Primary Investigator

Affiliation
Paderborn University

Other Primary Investigator(s)

PI Affiliation
Paderborn University
PI Affiliation
Leuphana University of Lueneburg

Additional Trial Information

Status
In development
Start date
2021-07-07
End date
2021-12-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
The project investigates the impact of social interactions on individuals' financial decision-making.
External Link(s)

Registration Citation

Citation
Krull, Sebastian, David Loschelder and Matthias Pelster. 2021. "Peer effects and financial decision-making I." AEA RCT Registry. September 17. https://doi.org/10.1257/rct.7896-1.1
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
The project investigates the impact of social interactions on individuals' financial decision-making.
Intervention Start Date
2021-07-07
Intervention End Date
2021-12-31

Primary Outcomes

Primary Outcomes (end points)
Inspired by the seminal work of Kahneman and Tversky (1979, 1992), we will observe the choices between either a risky lottery or a safe outcome for a list of decision problem. The sum of decisions that individuals have to make allows us to estimate the cash equivalents for different prospects and to quantify investors’ risk preferences.
Primary Outcomes (explanation)
The construction of primary outcome variables follows the original works by Kahneman and Tversky on Prospect Theory and Cumulative Prospect Theory (1979, 1992), respectively. The main variable of interest is the certainty equivalent, which is estimated as the mean value between the lowest accepted value of a certain outcome and its highest rejected value in a given decision problem.

Additionally, we will make use of the ratio of the certainty equivalent to the nonzero outcome of a prospect to fit smoothed curves for participants’ weighting functions (see Prospect Theory; Kahneman & Tversky, 1979).

Following the outline of Tversky & Kahneman (1992), we will first run the following analyses:
- Separately for gains and losses, we will use a nonlinear regression procedure to estimate parameters for the value function and the weighting function, separately for each participant. We will also report cumulative results for all estimated parameters.
- We will study the ratio(c/x) of the certainty equivalent(c) of the prospect to the nonzero outcome(x), as a function of the probability (p) to attain individual and cumulative weighting curves.

We will exclude inconsistent choices for any decision problem as they do not allow to determine the certainty equivalent for the respective prospect. We will also exclude participants who do not show a consistent pattern in their degree of risk aversion.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The project investigates the impact of social interactions on individuals' financial decision-making.
Experimental Design Details
Not available
Randomization Method
Participants will be randomly assigned to a treatment or control condition, with approximately 40 participants going to the control group (for each, the student and the professional sample). Participants in the treatment groups are randomly matched with their peers and therefore, receive a random level of treatment. Randomization will take place automated by oTree (Chen et al, 2016).
Randomization Unit
Randomization will take place on individual level.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
672 participants; 336 student participants and 336 professional participants.
Sample size: planned number of observations
672 participants; 336 student participants and 336 professional participants.
Sample size (or number of clusters) by treatment arms
We intend to sample 336 student participants and 336 professional participants. Given the design of the treatments, we cannot guarantee an equal distribution across treatment groups. Thus, we only assign approx. 40 of participants per sample (student and professional) to the control group; the remainder will be assigned to the treatment group and receive one of our treatments. As the exact treatment that individuals receive depends on their individual risk preferences prior to the treatment, we cannot ensure equal assignment to the three levels of treatment.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
We conducted an a-priori sample size analysis using G*Power (Faul, Erdfelder, Buchner, & Lang, 2009), based on the following parameters: α=.05, 1-β=.95, and a moderate population effect size of f=0.25 (d=0.50). Based on this sample size analysis (n=84, λ=15.75, Fcrit=3.03), we intend to recruit a total sample of 336 student participants and 336 professional participants, respectively.
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
University Paderborn Ethics Committee
IRB Approval Date
2020-09-07
IRB Approval Number
N/A
Analysis Plan

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