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Shifting Blame and Taking Credit

Last registered on April 14, 2020
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Pre-Trial

Trial Information

General Information

Title
Shifting Blame and Taking Credit
RCT ID
AEARCTR-0005640
Initial registration date
April 14, 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
April 14, 2020, 12:34 PM EDT

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

Locations

Country
Norway
Region

Primary Investigator

Name
Benny Geys
Affiliation
BI Norwegian Business School
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Other Primary Investigator(s)

PI Name
Martin Bækgaard
PI Affiliation
Aarhus University
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PI Name
Nanna Lauritz Schönhage
PI Affiliation
Vrije Universiteit Brussel
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Additional Trial Information

Status
In development
Start date
2020-06-01
End date
2022-12-31
Keywords
Electoral, Governance
Additional Keywords
JEL code(s)
Secondary IDs
Abstract
We study when and how local politicians shift the blame for negative policy outcomes and take credit for positive outcomes.
External Link(s)

Registration Citation

Citation
Bækgaard, Martin, Benny Geys and Nanna Lauritz Schönhage. 2020. "Shifting Blame and Taking Credit." AEA RCT Registry. April 14. https://doi.org/10.1257/rct.5640-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Interventions in terms of policy field, relevance and outcome.
Intervention Start Date
2020-06-01
Intervention End Date
2020-12-31

Primary Outcomes

Primary Outcomes (end points)
Politicians' blame-shifting and credit-taking.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Participants randomly allocated in a 2x2x2 experimental design with variation in terms of policy field, relevance and outcome.
Experimental Design Details
Participants will be randomly allocated in a 2x2x2 experimental design:
1. Two groups introducing two distinct policy fields with diverging levels of local ogvernment autonomy (primary education versus crime)
2. Two groups varying policy outcomes' electoral relevance: Explicit information about policy fields’ importance to the electorate versus no further information
3. Two groups varying in policy outcomes: positive versus negative frame for performance information
Randomization Method
Randomization done by computer
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
1200 individuals
Sample size: planned number of observations
1200 individuals
Sample size (or number of clusters) by treatment arms
150 individuals per treatment
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

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