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Learning about One's Self
Last registered on November 07, 2019

Pre-Trial

Trial Information
General Information
Title
Learning about One's Self
RCT ID
AEARCTR-0003060
Initial registration date
June 10, 2018
Last updated
November 07, 2019 3:35 PM EST
Location(s)
Region
Primary Investigator
Affiliation
University of Munich (LMU)
Other Primary Investigator(s)
PI Affiliation
University of Munich (LMU)
Additional Trial Information
Status
Completed
Start date
2018-06-11
End date
2018-06-28
Secondary IDs
Abstract
Previous studies document both present bias and people's naivete about being subject to present bias. However, it is puzzling that naivete that pertains to everyday behavior and a stable trait of the individual can persist. Why do people not learn about their bias? Our experiment seeks to provide a first step to resolving this puzzle empirically. We investigate whether people are able to learn about their present bias if they have the opportunity to engage in an unpleasant task repeatedly. To this end, we develop a framework that allows us to quantify what it means to learn optimally from one's own behavior and to compare individuals' observed learning to this benchmark.

In the experiment, subjects can complete two unpleasant tasks at two separate dates in the future. We elicit subjects' beliefs before and after the first task. During the first elicitation, we elicit a subject's joint prior distribution over her behavior at each of the two dates. After she either completes or fails to complete the first task, we elicit her beliefs about the likelihood of completing the second task. In a treatment, we vary whether the second task is the same task subjects completed at the first date, or a different one.

The resulting dataset allows us to study the extent to which people are able to learn from their past behavior. Moreover, we can investigate three potential drivers of people's failure to learn. First, people may underestimate how informative their behavior tomorrow is about their behavior the day after tomorrow. That is, they may not understand that behavior is driven by deep time preferences and, hence, underappreciate the correlation between their behavior at future dates. Second, people may interpret what task completion today implies for their task completion tomorrow in an upwardly biased way. To investigate this hypothesis, we ask whether a subject's belief after observing her task completion at the first date are compatible with her prior and its implied Bayesian posterior. Third, people may struggle to transport what they learn about their self-control problem in one environment into a (slightly) different environment. By varying the nature of the second task, we ask whether the previous two impediments to learning are more severe if the decision-making environment changes.
External Link(s)
Registration Citation
Citation
Schwardmann, Peter and Yves Yaouanq. 2019. "Learning about One's Self." AEA RCT Registry. November 07. https://doi.org/10.1257/rct.3060-2.1.
Former Citation
Schwardmann, Peter and Yves Yaouanq. 2019. "Learning about One's Self." AEA RCT Registry. November 07. https://www.socialscienceregistry.org/trials/3060/history/56644.
Experimental Details
Interventions
Intervention(s)
We investigate whether people are able to learn about their present bias if they have the opportunity to engage in an unpleasant task repeatedly. We develop a framework that allows us to quantify what it means to learn optimally from one's own behavior and to compare individuals' observed learning to this benchmark.

See pre-analysis plan for further details.
Intervention Start Date
2018-06-11
Intervention End Date
2018-06-28
Primary Outcomes
Primary Outcomes (end points)
Beliefs about task completion and implied naivite (Hypotheses 1, 3 and 5 ). Bias in perceived informativeness of behaviour (Hypotheses 2 and 4). See the pre-analysis plan for details on all of our measurements and the construction of key variables.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
See pre-analysis plan
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Subjects are given the opportunity to complete two unpleasant tasks at two separate dates in the future. We elicit subjects' beliefs before and after the first task. During the first elicitation, we elicit a subject's joint prior distribution over her behavior at each of the two dates. After she either completes or fails to complete the first task, we elicit her beliefs about the likelihood of completing the second task. In a treatment, we vary whether the second task is the same task subjects completed at the first date, or a different one.
Experimental Design Details
Randomization Method
All randomisations are done by a computer, either in real time or before the experiment starts.
Randomization Unit
Individual
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
200
Sample size: planned number of observations
200
Sample size (or number of clusters) by treatment arms
200
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
See pre-analysis plan
Supporting Documents and Materials

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Request Information
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Ethics Commission, Department of Economics, University of Munich.
IRB Approval Date
2018-05-23
IRB Approval Number
2018-03
Analysis Plan
Analysis Plan Documents
PAP_Learning about one_s self.pdf

MD5: 449128d977f8847b6dbd9708edf288bd

SHA1: 818e2337e603631e86132a5d995a70ec8a7f9297

Uploaded At: June 10, 2018

PAP Follow up.pdf

MD5: 216448189c5b7a8c7c07e9bb666442a9

SHA1: 11901906ef204c392a0e855d2f7315987ae1843d

Uploaded At: November 07, 2019

Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
No
Is data collection complete?
Data Publication
Data Publication
Is public data available?
No
Program Files
Program Files
Reports and Papers
Preliminary Reports
Relevant Papers