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Narrow Bracketing in Effort Choices
Last registered on October 11, 2019

Pre-Trial

Trial Information
General Information
Title
Narrow Bracketing in Effort Choices
RCT ID
AEARCTR-0003412
Initial registration date
January 07, 2019
Last updated
October 11, 2019 12:57 AM EDT
Location(s)

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Primary Investigator
Affiliation
Luxembourg Institute of Socio-Economic Research
Other Primary Investigator(s)
PI Affiliation
Central European University
Additional Trial Information
Status
In development
Start date
2019-10-09
End date
2020-02-29
Secondary IDs
Abstract
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
Citation
Fallucchi, Francesco and Marc Kaufmann. 2019. "Narrow Bracketing in Effort Choices." AEA RCT Registry. October 11. https://doi.org/10.1257/rct.3412-3.0.
Former Citation
Fallucchi, Francesco and Marc Kaufmann. 2019. "Narrow Bracketing in Effort Choices." AEA RCT Registry. October 11. https://www.socialscienceregistry.org/trials/3412/history/54947.
Experimental Details
Interventions
Intervention(s)
We test the concept of narrow and broad bracketing in deterministic choices over work, which are relevant to the labor market.
Intervention Start Date
2019-10-09
Intervention End Date
2020-02-29
Primary Outcomes
Primary Outcomes (end points)
See october-2019-design.pdf for change in design.

The following previous design description is included for completeness, but is *NOT* what we are currently planning on running.

Elicitation of the willingness to accept a payment in order to complete a task across different treatments. Thus the questions are two, linked to the framing of doing extra work: the first concerns doing extra work after a (changing) fixed mandatory work; the second 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. We will compare this to choices where we enforce broad bracketing, by making the actual change salient.
Primary Outcomes (explanation)
See october-2019-design.pdf for change in design.

The following previous design description is included for completeness, but is *NOT* what we are currently planning on running.

In each treatment we will ask subjects to complete a required task and then elicit their willingness to complete extra tasks. We will compare in each treatment the total number of tasks performed.
Secondary Outcomes
Secondary Outcomes (end points)
See october-2019-design.pdf for change in design.

The following previous design description is included for completeness, but is *NOT* what we are currently planning on running.

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. We will test whether people make the same mistake when they see both choices, controlling for an order effect.
Secondary Outcomes (explanation)
See october-2019-design.pdf for change in design.

The following previous design description is included for completeness, but is *NOT* what we are currently planning on running.

It may be that people bracket narrowly, but not if they see the broadly bracketed version first. Thus a person who is asked for their WTW for 20 tasks rather than 10, and then asked for their willingness to do 10 tasks before doing the 20, may realize that these questions are the same, and thus broadly bracket the second question. If asked first for their WTW for 10 tasks before 10, and then for their WTW 20 rather than 10, their answer to the "10 before 10" may be different because they did not realize that it is about doing 20 rather than 10 tasks. Thus we want to measure whether the same question leads to different answers depending when people are asked the question.

Since one concern is that people may either use heuristics to make decisions faster ("This is 10 extra tasks, so I'll give the same answer as before") or want to be consistent with their past choices once they realize they are the same ("Oh, 20 vs 10 tasks is the same as my previous answer, I should give the same answer") rather than admit they might have gotten it wrong (Augenblick and Rabin (2018) do find that this effect is quite strong in their experiment, when subjects are reminded of their past choice) this will not cleany establish which choice people think is a mistake, but together with the between-subjects design it should shed light on it.

Ignoring these other concerns (heuristics, desire for consistency), we will use these answers to create a measure of narrow bracketing at the individual level: the degree to which the BROAD answer is different from the NARROW answer, and we'll do so accounting for order effects.

The reason for testing correlation between individual-level narrow bracketing in our context and in risky choices (based on our within-subjects treatment) is straightforward: we want to see if there are people who are more likely to narrow bracket in different types of settings.
Experimental Design
Experimental Design
In an online 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 Mturk.
Randomization Unit
Individual
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
Experiment on MTurk.
Sample size: planned number of observations
450 for the one-day design. 2-day design needs fleshing out.
Sample size (or number of clusters) by treatment arms
90 for each of the four main treatments, 45 for the minor treatments. See october-2019-design.pdf for details.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Assuming a similar level of narrow bracketed individuals across treatments, for a given uniform distribution among the WTA the expected effect size between total task in the two NARROW treatments is d=1.10. As this may seems little conservative we plan to collect a total of 90 subjects per treatment, that would give us a 90% power to detect the effect size at the 5% level of significance for an effect size of 0.5. The same number of observations will be collected for the BROAD treatments, where we expect no difference in the total number of tasks. Based on an expected effect size d = 0.4 we assign 140 observations to each of the two treatments for our main comparison between NARROW BEFORE and NARROW AFTER, if we end up running this design (see october-2019-design.pdf). This would give us 90% power to detect the effect size at the 5% level of significance.
Supporting Documents and Materials

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IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
CEU Ethical Research Committee
IRB Approval Date
2018-08-13
IRB Approval Number
2017-2018/11/EX