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Demand for Commitment in Volunteering
Last registered on March 15, 2021


Trial Information
General Information
Demand for Commitment in Volunteering
Initial registration date
March 12, 2021
Last updated
March 15, 2021 10:50 AM EDT
Primary Investigator
Boston College
Other Primary Investigator(s)
Additional Trial Information
In development
Start date
End date
Secondary IDs
One of the key determinants of commitment demand is perceived present bias. The direction and magnitude of the effect of informing individuals of their present bias are ambiguous and remain an empirical question. The effect of correcting beliefs on present bias on commitment demand is an important determinant of whether commitment devices are an appropriate policy tool, and whether their success depends on improving self awareness of present bias. I will study the effect of updating beliefs about present bias on commitment demand in the setting of decisions to volunteer. Volunteering has been shown to be strongly associated with improved happiness and subjective well-being; however, the "warm glow" of prosocial behavior often comes after costly effort, making the decision to volunteer susceptible to present bias. This study will therefore also provide insight into how to improve both volunteerism rates and subjective well-being of individuals.
External Link(s)
Registration Citation
Westphal, Ryan. 2021. "Demand for Commitment in Volunteering." AEA RCT Registry. March 15. https://doi.org/10.1257/rct.7315-1.0.
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Experimental Details
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
Willingness to pay for commitment
Volunteering rates
Primary Outcomes (explanation)
Willingness to pay for commitment is measured by switching points in the BDM mechanism
Volunteering rates are based on photo evidence when incentivized, and survey responses when unincentivized.
Secondary Outcomes
Secondary Outcomes (end points)
Beliefs about present bias and likelihood of volunteering
Secondary Outcomes (explanation)
Subjects are asked the probability that they volunteer in the next month
They are also asked how much they procrastinate relative to other students
Experimental Design
Experimental Design
To measure willingness to pay for a commitment device (defined as receiving payment conditional on following through and volunteering in the next month rather than unconditional payment), I will use the Becker, Degroot, Marschak (BDM) Mechanism (1964). Subjects will be asked if they would rather have X dollars unconditionally or 25 dollars conditional on volunteering with a non-profit organization at least once in the next month. Then one of these decisions is chosen at random and implemented.

To measure the effect of information on this willingness to pay, I will have a treatment group who is given information about their present bias as measured by the first stage of the study. Subjects will be told whether our model predicts that they are present biased, and if so, whether our model predicts that they will struggle with procrastination in volunteering. We will then measure the differences in willingness to pay for commitment between the control and treatment groups. To measure the effect of commitment devices on volunteering decisions, a treatment group will receive their choice of an unconditional payment and the commitment device from the BDM mechanism. The control group will receive an unconditional payment no matter their decision. We will then follow up with all subjects during the next month about volunteering decisions with an incentivized survey. All subjects who received the unconditional payment will be asked to self report whether or not
they volunteered.
Experimental Design Details
Not available
Randomization Method
Random number generator in Qualtrics
Randomization Unit
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
240 students
Sample size: planned number of observations
240 students.
Sample size (or number of clusters) by treatment arms
Individuals have a 50% chance of being selected for both the information treatment and the incentive treatment. So both treatments have roughly 120 students in the control group and 120 students in the treatment group.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
The minimum detectable effect size is approximately $0.5 change in willingness to pay for commitment. This is calculated using a standard deviation of willingness to pay of $1.40 which is approximated from a pilot survey.
IRB Name
Boston College Institutional Review Board
IRB Approval Date
IRB Approval Number