Decomposing Trust

Last registered on November 18, 2021

Pre-Trial

Trial Information

General Information

Title
Decomposing Trust
RCT ID
AEARCTR-0005146
Initial registration date
December 10, 2019
Last updated
November 18, 2021, 2:41 AM EST

Locations

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Primary Investigator

Affiliation
Lund University

Other Primary Investigator(s)

PI Affiliation
HU Berlin
PI Affiliation
DIW and HU Berlin
PI Affiliation
HU Berlin

Additional Trial Information

Status
In development
Start date
2019-12-11
End date
2022-12-01
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Trust is thought to be an important driver of economic growth and other economic outcomes. Previous studies suggest that trust may be a combination of risk attitudes, social preferences, betrayal aversion, and beliefs about the probability of being reciprocated. We compare the results of a binary trust game to the results of a series of control treatments that remove the effects of one of or more of these components of trust by design. This allows us to decompose variation in trust behavior into its underlying factors. We will compare our results to previous studies that use different methods to decompose trust, and also decompose the drivers of a potential gender difference in trust, should one emerge.
External Link(s)

Registration Citation

Citation
Engelmann, Dirk et al. 2021. "Decomposing Trust." AEA RCT Registry. November 18. https://doi.org/10.1257/rct.5146-1.2000000000000002
Experimental Details

Interventions

Intervention(s)
We compare the results of a binary trust game to the results of a series of within-subject control treatments that remove the effects of individual explanatory factors of trust (or combinations thereof) by design.
Intervention Start Date
2019-12-11
Intervention End Date
2019-12-18

Primary Outcomes

Primary Outcomes (end points)
Trust and trust-equivalent decisions
Primary Outcomes (explanation)
Trust-equivalent decisions are the binary choices in the control treatments that are similar to the binary trust game but iteratively remove the effect of one of the explanatory factors of trust behavior by design.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We investigate choices in a laboratory experiment in a binary trust game. We compare the choices in a standard game with choice lists that condition on the number of reciprocating players (or a corresponding lottery). These choice lists systematically vary whether social preferences, risk preferences and betrayal aversion should have an impact. We also elicit beliefs about the number of reciprocating participants in the session and independent measures of risk and social preferences.
Experimental Design Details
Not available
Randomization Method
Computer
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
200 Individuals
Sample size: planned number of observations
200 Individuals
Sample size (or number of clusters) by treatment arms
200 individuals per treatment arm (this is a within-subject design).
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
See the pre-analyis plan.
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

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