Candidate Entry into Local Government

Last registered on September 07, 2022

Pre-Trial

Trial Information

General Information

Title
Candidate Entry into Local Government
RCT ID
AEARCTR-0010006
Initial registration date
August 31, 2022

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
September 07, 2022, 3:44 PM EDT

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

Locations

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Primary Investigator

Affiliation
Stanford GSB

Other Primary Investigator(s)

PI Affiliation
IGC
PI Affiliation
IGC
PI Affiliation
Stanford University

Additional Trial Information

Status
In development
Start date
2022-09-01
End date
2024-12-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This research project tackles the governance challenge of getting high human capital, high integrity, representative citizens to put themselves forward for consideration as political candidates. We plan to explore potential solutions to this challenge with our partners in government and civil society in connection with the 2023 Local Council Elections in Sierra Leone. To do so we propose an initiative that would: i) identify, screen, and encourage high quality potential candidates to enter politics; and ii) share information about these potential candidates with political parties. We plan to randomize this initiative across 150 of 300 local government wards to assess impacts on the pool of aspirants, selected candidates, and elected officials. Additionally, inside the set of treated wards, we propose a sub-experiment focused on increasing female representation in politics. This will explore barriers to female participation emanating from voters, party elites and potential candidates themselves.
External Link(s)

Registration Citation

Citation
Casey, Katherine et al. 2022. "Candidate Entry into Local Government." AEA RCT Registry. September 07. https://doi.org/10.1257/rct.10006-1.0
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2022-10-01
Intervention End Date
2023-08-01

Primary Outcomes

Primary Outcomes (end points)
size, quality and representativeness of aspirant pool; quality and representativeness of selected candidates
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
quality and representativeness of elected officials
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The intervention will be randomized across local government wards, with an embedded sub-experiment focused on women in politics
Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer
Randomization Unit
Political party - ward units
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
300 party-wards
Sample size: planned number of observations
300 aspirant pools, 300 selected candidates
Sample size (or number of clusters) by treatment arms
150 treated wards 150 control wards
Within treated wards, 3 sub-arms
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
Stanford University
IRB Approval Date
2022-07-26
IRB Approval Number
64314