Consent and Information Disclosure: An Experiment

Last registered on June 12, 2024


Trial Information

General Information

Consent and Information Disclosure: An Experiment
Initial registration date
July 13, 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, 2:30 PM EDT

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

Last updated
June 12, 2024, 2:35 AM EDT

Last updated is the most recent time when changes to the trial's registration were published.


There is information in this trial unavailable to the public. Use the button below to request access.

Request Information

Primary Investigator

Deakin University

Other Primary Investigator(s)

PI Affiliation
Monash University
PI Affiliation
Monash University

Additional Trial Information

On going
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Economic transactions may lead to disputes where the weaker party claims economic abuse or injury. A key consideration for whether policy or legislation should intervene is a lack of consent from the weaker party. An important element of consent is the information state of the weaker party at the time of transacting. With decreasing costs of information disclosure, this has led to governments, firms, and legislators inundating consumers with pre-transactional information (or mandating for it to be so). For example, mandatory disclosure "is among the most ubiquitous and least controversial elements of public policy, often promoted as an attractive alternative to so-called hard forms of regulation" (Loewenstein et al, 2014). The appeal of information disclosure stems from the general presumption that while more information may not necessarily help, it cannot make things worse for consumers. Motivated by literatures on blame, counterfactual thinking, and the psychology of consent, we explore avenues through which information disclosure may make things worse for the consumer. We consider how information disclosure affects both society (through third-party spectators) and the stronger party’s interpretations of the extent the consumer is believed to have consented to the outcomes, an issue that has received little scrutiny in the economics literature.
External Link(s)

Registration Citation

Chaudhury, Ratul, Aaron Nicholas and Birendra Rai. 2024. "Consent and Information Disclosure: An Experiment." AEA RCT Registry. June 12.
Experimental Details


We investigate:
(a) whether third-party spectators attach significance to “consumers” reading “contractual fine print”, even when such information is not pivotal to the consumer’s decision making.
(b) whether information disclosure provides a moral license to “firms” or instead encourages them to behave more fairly (a telltale heart effect [1]) when the firm is powerful and hence when information is not pivotal to the consumer’s decision making;
To investigate these questions, we adopt an online experiment via a Qualtrics survey distributed through Prolific. Our design involves a variant of the Yes/No version of the ultimatum game [2], where the first mover receives positive payoff even upon rejection. For question (a), we utilise the third-party spectators’ willingness to redistribute earnings in favour of the consumer in situations where the firm behaves opportunistically. For question (b), we utilise the firm’s offer to the consumer. We supplement this with elicitation of third-party spectators’ and firms’ interpretation of whether consumers consented to the exchange. This is incentivised using the Krupka and Weber [3] method.

[1] Loewenstein, G., Sunstein, C. R., & Golman, R. (2014). Disclosure: Psychology changes everything. Annu. Rev. Econ., 6(1), 391-419.
[2] Gehrig, T., Güth, W., Levati, V., Levínský, R., Ockenfels, A., Uske, T., & Weiland, T. (2007). Buying a pig in a poke. Journal of Economic Psychology, 28(6), 692–703.
[3] Krupka, E. L., & Weber, R. A. (2013). Identifying social norms using coordination games: Why does dictator game sharing vary?. Journal of the European Economic Association, 11(3), 495-524.

Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
PC’s choice of [ (15, 5); (11, 6); (9, 6) ] across treatments and within the information treatment (i.e. conditional on PB having checked, versus not checked PA’s offer).
PA’s choice of [9 or 5] across treatments.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Normative Expectation questions related to consent. This variable will be compared across treatments, as well as within the information treatment as per the primary outcome for PC. In addition, this variable will be compared across participant roles. As each role receives the same question we can check if the interpretation of consent varies across roles within the same treatments.
The relevant question in the baseline is as follows:
PA offers 5 out of 20 to PB.
PB accepts, without knowing that PA offered 5.
Do you agree/disagree with the following statement?
“PB consented to their earnings of 5.”
Choices: (Strongly agree); (Somewhat agree); (Neither agree nor disagree); (Somewhat disagree); (Strongly disagree)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Baseline (no information treatment)
• Pie size of 20
• Player A (PA) can offer 9 or 5 to PB and keep the remainder
• Player B (PB) can reject or accept without knowing the offer.
Rejection payoffs: (12 for PA, 0 for PB)
Acceptance payoffs: as per offer by PA
• If PA offered 5 and PB accepted, Player C (PC) is given a chance to decide the final payoffs for PA and PB. PC chooses one of the following three:
(15, 5); (11, 6); (9, 6)
PC is a spectator and their decision does not affect their own payoff.
• After these decisions, each player is given the same set of questions on Beliefs, Normative Expectations and demographic questionnaire. The Beliefs and Normative Expectations questions are incentivised. The latter is incentivised using the Krupka and Weber (2013) method.
• Normative Expectation questions related to consent will be used as a secondary outcome variable.

Information treatment
The only difference between the baseline and information treatment is that prior to deciding whether to accept or reject the offer, PB can choose to check or not check the offer by PA. To check, PB has to complete a decoding task that takes on average, 2-3 minutes of their time. If the task is completed, PB finds out what PA offered prior to deciding to reject or accept the offer. Otherwise, PB chooses as per the baseline treatment.

*Please refer to 'Experimental Design (Hidden)' for planned additions in May 2024
Experimental Design Details
Not available
Randomization Method
Recruitment is done on Prolific
Randomization Unit
Prolific’s demographic balancing feature will be used to ensure a 50/50 split between male and female participants. Participants are restricted to having completed high school and being between 18—50 years old.
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
Not clustered.
Sample size: planned number of observations
900 participants from Prolific
Sample size (or number of clusters) by treatment arms
450 baseline treatment; 450 information treatment. As each treatment has three roles, there are 150 observations per role, for each treatment.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
Monash University Human Research Ethics Committee
IRB Approval Date
IRB Approval Number