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Narrow Bracketing in Effort Choices
Last registered on January 25, 2019


Trial Information
General Information
Narrow Bracketing in Effort Choices
Initial registration date
January 07, 2019
Last updated
January 25, 2019 3:31 AM EST
Primary Investigator
Luxembourg Institute of Socio-Economic Research
Other Primary Investigator(s)
PI Affiliation
Central European University
Additional Trial Information
In development
Start date
End date
Secondary IDs
Narrow bracketing has been established in choices over risky gambles, but not outside of it, even in natural situations such as the working environment. Many decisions people take, such as deciding whether to do an urgent, but not particularly important task right now, have low immediate costs – checking emails – but may have large costs later on, such as requiring one to work late when tired to make up the lost time. While sometimes people may take such decisions in full awareness of these implications – either because it is the ‘right/rational’ decision, or because they are present-biased – it may also be due to not thinking about these future implications. Narrow bracketing is a specific way of not thinking about these implications, and we test for it in a situation where preferences, properly thought through, cannot cause such mistakes, even when people are present-biased.
External Link(s)
Registration Citation
Fallucchi, Francesco and Marc Kaufmann. 2019. "Narrow Bracketing in Effort Choices." AEA RCT Registry. January 25.
Former Citation
Fallucchi, Francesco, Francesco Fallucchi and Marc Kaufmann. 2019. "Narrow Bracketing in Effort Choices." AEA RCT Registry. January 25.
Experimental Details
We test the concept of narrow bracketing in deterministic choices over work, which are relevant to the labor market.
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
Elicitation of the willingness to accept a payment in order to complete a task across different treatments. Thus the question is whether the framing as doing extra work 'before' rather than 'after' - while holding the actual consequences constant - leads to a change in willingness to work, which it cannot under any broadly framed theory.
Primary Outcomes (explanation)
We will ask subjects at what price they will be willing to complete a task, based on a piece-rate payment. We will elicit their choices in two different ways.
Secondary Outcomes
Secondary Outcomes (end points)
We want to measure whether there is a correlation between subject's level of narrow bracketing in deterministic work choices and narrow bracketing in risky choices; whether there is more narrow bracketing when the metrics for the extra work is different from the metric for the main work (that is, it is expressed as a piece-rate, $0.40 per task, rather than $4 for doing 10 tasks), compared to when the metric is the same. A further analysis will be done on an extra within subjects treatment, where both before/after choices will be proposed. We will test whether people make the mistake when they see both choices, controlling for an order effect.
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
In a laboratory experiment, using a real effort task, we measure whether psychological factors affect the decisions to work extra time.
Experimental Design Details
Not available
Randomization Method
Randomization done throughout the recruitment platform Orsee on a students' subject pool from the University of Luxembourg.
Randomization Unit
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
380 student subjects recruited throughout orsee (Greiner, 2015), 280 for the two main between-subjects treatments and 100 for the within-subjects treatment.
We will initially conduct the two main treatments. The within-subjects will be built as a follow up.
Sample size: planned number of observations
380 student subjects recruited throughout orsee (Greiner, 2015)
Sample size (or number of clusters) by treatment arms
140 subjects for each of the two between subjects treatments (80 with the slider elicitation methods and 60 with the price list) and 100 subjects in the within subjects treatment.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Based on an expected effect size d = 0.4 we assign 140 observations to each of the two treatments. This gives us 90% power to detect the effect size at the 5% level of significance.
IRB Name
CEU Ethical Research Committee
IRB Approval Date
IRB Approval Number