Acceptance Towards Corruption

Last registered on May 18, 2023
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Pre-Trial

Trial Information

General Information

Title
Acceptance Towards Corruption
RCT ID
AEARCTR-0006669
Initial registration date
October 26, 2020

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
October 27, 2020, 7:15 AM EDT

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

Last updated
May 18, 2023, 7:54 AM EDT

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

Locations

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Primary Investigator

Name
Matteo Francesco Ferroni
Affiliation
Boston University
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Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2020-10-28
End date
2024-05-31
Keywords
Behavior, Crime, Violence, & Conflict, Electoral
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
I estimate how much individuals are willing to accept corruption and how this acceptance threshold can be influenced by their environment.
Through an online survey, I ask respondents if they are willing to vote for a certain competent politician who embezzled some money or not. By changing the amount of money embezzled I am able to estimate the threshold level at which each respondent is still willing to vote for that given politician.
To identify possible causes that affect this acceptance level, I conduct different experiments during the survey. The first experiment looks at the impact of others' acceptance on your own. The second experiment investigate how a perceived higher frequency of corruption affects your acceptance level.
I also provide descriptive results on how the acceptance level correlates with various background characteristics of the respondents. Asking question also on policy preferences, will allow me to see how various level of acceptance are correlated with these preferences. I also shows some evidence on how thinking about corruption may affect the preferences on the role and size of the government.
External Link(s)

Registration Citation

Citation
Ferroni, Matteo Francesco. 2023. "Acceptance Towards Corruption." AEA RCT Registry. May 18. https://doi.org/10.1257/rct.6669-1.3
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
I elicit respondents’ acceptance level of corruption, their attitudes and views about corruption, and their preferences for various policies, as well as their perception of other people’s attitudes. In a randomized way, I provide respondents with information about other people’s acceptance level of corruption, or I prime them to perceive corruption as more frequent by showing them newspaper headlines on corruption scandals.
Intervention Start Date
2020-10-28
Intervention End Date
2020-12-31

Primary Outcomes

Primary Outcomes (end points)
I’m interested in i) individuals’ acceptance of corruption, ii) individuals’ perception of other’s acceptance of corruption, iii) attitudes and views about corruption such as seriousness and frequency, iv) policy preferences
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
I will randomize the treatments assigned to the respondents. One group will see newspaper headlines on corruption scandals; a second group will see the acceptance level of corruption of various groups of respondents; a third group is the control group and sees no information. I also randomize the order in which the questions on preferences for redistribution policy appear: one group will answer to them at the beginning of the survey, a second group at the end.
Experimental Design Details
Not available
Randomization Method
Randomization done by Qualtrics
Randomization Unit
Individual level
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
5000 individuals
Sample size: planned number of observations
5000 individuals
Sample size (or number of clusters) by treatment arms
1,750 control individuals,
1,250 treated with newspaper headlines,
1,000 treated with information on Democrats' answers,
1,000 treated with information on Republicans' answers.

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
Charles River Campus Institutional Review Board
IRB Approval Date
2020-10-08
IRB Approval Number
3732X
Analysis Plan