Why does locus of control influence behaviour?

Last registered on March 12, 2021
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Pre-Trial

Trial Information

General Information

Title
Why does locus of control influence behaviour?
RCT ID
AEARCTR-0007317
Initial registration date
March 11, 2021

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
March 12, 2021, 8:47 AM EST

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

Locations

Country
Australia
Region

Primary Investigator

Name
Juliana Silva Goncalves
Affiliation
University of Sydney
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Arne Uhlendorff
PI Affiliation
ENSAE
Contact Investigator
PI Name
Marco Caliendo
PI Affiliation
Potsdam University
Contact Investigator
PI Name
Deborah Cobb-Clark
PI Affiliation
The University of Sydney
Contact Investigator

Additional Trial Information

Status
In development
Start date
2021-03-22
End date
2022-06-30
Keywords
Behavior
Additional Keywords
Locus of control, Decision-making, Laboratory experiment
JEL code(s)
D91
Secondary IDs
Abstract
Locus of control is a personality trait that defines one’s general belief regarding the nature of the causal relationship between own behaviour and experienced outcomes (Rotter, 1966). Those believing that life outcomes are due to their own efforts have an internal locus of control, while those believing they are due to external circumstances, such as luck, have an external locus of control. Research revealed an association between having an internal locus of control and behaving in way that is conducive to desirable outcomes in several domains of life including education, health, employment, finances and parenting.
We will investigate the underlying relationship between locus of control and life outcomes by establishing the link between locus of control and the determinants of decision-making. Specifically, we will establish the predictive power of locus of control measured with a self-reported psychometric scale and a set of economic preferences and beliefs that guide decision-making and are conceptually related to locus of control. These include the preference for agency, optimism about returns from effort, self-confidence and the illusion of control. They will be elicited in a laboratory environment with incentivised tasks and in a unified context of decision-making.
External Link(s)

Registration Citation

Citation
Caliendo, Marco et al. 2021. "Why does locus of control influence behaviour?." AEA RCT Registry. March 12. https://doi.org/10.1257/rct.7317-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2021-03-22
Intervention End Date
2021-12-31

Primary Outcomes

Primary Outcomes (end points)
They have been specified in the analysis plan.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
They have been specified in the analysis plan.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We will measure locus of control using the Psychological Coping Resources component of the Mastery Module developed by Pearlin and Schooler (1978). We will measure the decision-making parameters using the delegation game introduced by Bartling et al. (2014) as well as a modified version of the game. The full description of our experimental design is provided in the analysis plan.
Experimental Design Details
Randomization Method
We conduct a laboratory experiment on decision-making, which does not entail a 'control' and a 'treatment' group. We have two treatments in a between-subjects design, each treatment measuring different aspects of decision-making. The treatment is randomly assigned to participants by a computer at the session level.
Randomization Unit
Treatments are assigned randomly at the experimental session level.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
Not applicable.
Sample size: planned number of observations
300 (see our analysis plan for details on sample size).
Sample size (or number of clusters) by treatment arms
150 (see our analysis plan for details on sample size).
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Specified in the analysis plan.
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
The University of Sydney Ethics Committee
IRB Approval Date
2019-11-07
IRB Approval Number
2019/856
Analysis Plan

Analysis Plan Documents

Analysis+plan.docx

MD5: 09b0efd42fc62f1e02bcc53fdd784fcd

SHA1: eb1d0314b4c84ee0453885d32e87d84621ed3417

Uploaded At: March 11, 2021

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials