Choice Architecture for Messaging Corruption

Last registered on March 12, 2021
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Pre-Trial

Trial Information

General Information

Title
Choice Architecture for Messaging Corruption
RCT ID
AEARCTR-0007233
Initial registration date
March 11, 2021

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
March 12, 2021, 8:48 AM EST

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

Locations

Country
Chile
Region

Primary Investigator

Name
Felipe Torres
Affiliation
University of Oxford
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Other Primary Investigator(s)

PI Name
Raymond Duch
PI Affiliation
Nuffield College
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Additional Trial Information

Status
In development
Start date
2021-03-01
End date
2021-03-31
Keywords
Electoral, Governance
Additional Keywords
Corruption
JEL code(s)
P48; D73
Secondary IDs
FONDECYT - Chile
Abstract
We study to what information and benchmark voters update beliefs regarding corruption when they are presented with ``objective'' information about malfeasance. We conducted and mixed within-between subjects design, where respondents will receive different information about corruption using different benchmarks. The treatment consists of 6 short videos with different information about malfeasance.

For all video treatments, we will measure beliefs about the prevalence of corruption using different metrics 1) beliefs about the prevalence of corruption using a 0 - 10 scale; 2) beliefs about the prevalence of corrupt behavior by civil servants in that local government; and 3) beliefs about the economic impacts of corruption.
External Link(s)

Registration Citation

Citation
Duch, Raymond and Felipe Torres. 2021. "Choice Architecture for Messaging Corruption." AEA RCT Registry. March 12. https://doi.org/10.1257/rct.7233-1.0
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
We will conduct a factorial design, where respondents will receive different information about corruption using different benchmarks. The treatment consists of 6 short videos with different information about malfeasance.

For all video treatments, we will measure beliefs about the prevalence of corruption using different metrics 1) beliefs about the prevalence of corruption using a 0 - 10 scale; 2) beliefs about the prevalence of corrupt behaviour by civil servants in that local government; and 3)beliefs about the economic impacts of corruption. Further details can be found in our pre-analysis plan.
Intervention Start Date
2021-03-10
Intervention End Date
2021-03-27

Primary Outcomes

Primary Outcomes (end points)
1) Beliefs about corruption using a 0 to 10 scale
2) beliefs about the prevalence of corrupt behaviour by civil servants in that local government,
and 3) beliefs about the economic impacts of corruption
4) Beliefs about the location o
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
No secondary outcomes
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We will implement a factorial design that generates 24 treatment conditions. Respondents will receive the information using six different metric dimensions: standard, severity, resources total, resources individual, resources foregone losses, and program; two benchmarking dimensions: spatial and temporal; and two valence dimensions: positive and negative performance. Hence we have a 6 X 2 X 2 factorial design. There are a total of 24 factorial cells. Further details can be found in our pre-analysis plan.
Experimental Design Details
Further details can be found in our pre-analysis plan.
Randomization Method
Simple randomization from a web service: random.org
Randomization Unit
Individuals
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
None
Sample size: planned number of observations
9000 number of observations collected from at least 1500 respondents
Sample size (or number of clusters) by treatment arms
At least 1500
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
According to our power calculations simulations, 2 of the 5 treatments will be powered at a 0.8 level with 1,500 respondents
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
SOCIAL SCIENCES & HUMANITIES INTERDIVISIONAL RESEARCH ETHICS COMMITTEE
IRB Approval Date
2020-03-31
IRB Approval Number
R68234/RE001
Analysis Plan

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Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials