Information and Charitable Giving

Last registered on July 19, 2023


Trial Information

General Information

Information and Charitable Giving
Initial registration date
July 10, 2023

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
July 19, 2023, 12:26 PM EDT

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


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Primary Investigator


Other Primary Investigator(s)

PI Affiliation
PI Affiliation

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
In this research, our goal is to explore the distribution of donor types within a donor population. Our method includes comparing situations where participants have full knowledge of all theoretically important variables for a donation decision with those where such information needs to be gathered. Based on standard theories of giving, we predict which type of donor should seek out which specific pieces of information. Upon obtaining the required information, participants decide the amount of money they wish to donate to a single charity recipient they have been paired with. After classifying donor types, our focus shifts to understanding how the way we present information influences donations, how different donor types react to changes in policy variables (such as rebate and match rates) and how income shifts affect donations.
External Link(s)

Registration Citation

Arroyos-Calvera, Danae, Johannes Lohse and Kimberley Scharf. 2023. "Information and Charitable Giving." AEA RCT Registry. July 19.
Experimental Details


Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
- Giving at the extensive/intensive margin i.e., how much of their own income participants donate to the charitable recipient
- Total amount received by the charitable recipient
- Information gathered (in the information choice treatments)
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
In total, we compare four experimental treatments (between subjects) that vary which information participants have before making a donation decision. The design is based on standard theories of giving which posit that donors care about the total amount received by a recipient (G), their personal income (x) and their donation (g) as well as the share of their impact (g/G). The weight of these variables depends on the donor type (i.e., their unknown utility function). In a minimal design, we provide subjects with information about g and x, as well as about an amount committed by a third party. This follows a design in Ottoni-Wilhelm et al (2017). In an expanded version of the design, we provide a further breakdown of these information variables and hence allow different giving types to express their preferences more fully. The main focus for identifying giving types is on two treatments where participants have to decide which information they want to gather (for free) prior to making a decision.

Within subjects the choice sets vary
- The amount committed by a third party
- The amount of the gift matched/rebated
- The total income participants can choose over

In total each participant will provide answers in 16 main choice sets with 6 possible allocations in each. We also include 8 filler tasks.
Experimental Design Details
Not available
Randomization Method
Between subjects, participants are randomized to one of four treatments.
Within subjects, participants will encounter 16 choice problems. They will first encounter all rebate or all match questions; this is randomised on a per-subject basis. Within the rebate or match choices block, the order of the choices is also randomised on a per-subject basis. The filler choices always appear in the same order within each block.
Randomisation is dealt with via a computer program.
Randomization Unit
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
Sample size: planned number of observations
We plan to collect a total of 800 observations.
Sample size (or number of clusters) by treatment arms
200 participants per each of the 4 treatment arms.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
This allows us (depending on the respective question) to identify medium sized to small effect sizes.

Institutional Review Boards (IRBs)

IRB Name
University of Birmingham
IRB Approval Date
IRB Approval Number