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Registering Re-Entering Citizens to Vote

Last registered on June 30, 2020

Pre-Trial

Trial Information

General Information

Title
Registering Re-Entering Citizens to Vote
RCT ID
AEARCTR-0004574
Initial registration date
August 13, 2019

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
August 13, 2019, 5:09 PM EDT

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

Last updated
June 30, 2020, 1:49 PM EDT

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

Locations

Primary Investigator

Affiliation
MIT

Other Primary Investigator(s)

PI Affiliation
Texas A&M
PI Affiliation
Alloy
PI Affiliation
Denver University
PI Affiliation
Yale University
PI Affiliation
Rutgers

Additional Trial Information

Status
In development
Start date
2019-08-28
End date
2021-02-01
Secondary IDs
Abstract
Millions of people in the US are eligible to vote despite past felony convictions, but their voter participation rates are extraordinarily low. Efforts to register and mobilize this population have foundered due to data limitations. In this pilot project, we will test a method for registering previously-convicted or formerly-incarcerated people to vote. We propose to use administrative data to identify and find contact information for people with past convictions, and then to send them messages encouraging them to register. This pilot study will lay the groundwork for a larger experiment. Ultimately, we plan a large randomized control trial to test the efficacy of such contacts for converting returning citizens into registered voters. This type of evidence is especially important as states consider restoring voting rights to individuals with felony convictions who remain disenfranchised.
External Link(s)

Registration Citation

Citation
Doleac, Jennifer et al. 2020. "Registering Re-Entering Citizens to Vote." AEA RCT Registry. June 30. https://doi.org/10.1257/rct.4574-2.0
Former Citation
Doleac, Jennifer et al. 2020. "Registering Re-Entering Citizens to Vote." AEA RCT Registry. June 30. https://www.socialscienceregistry.org/trials/4574/history/71622
Experimental Details

Interventions

Intervention(s)
We will contact previously-convicted people prior to fall municipal elections, offering them information about eligibility to vote and a registration form and stamped envelope to return that form to the board of elections.

We will scale up the previous pilot study for a larger trial prior to the 2020 general election. We will use a between-subjects design with several treatment arms and an (uncontacted) control group.
Intervention Start Date
2019-08-28
Intervention End Date
2020-11-03

Primary Outcomes

Primary Outcomes (end points)
Voter registration (appearing on the state's public voter file) and voting in municipal elections where relevant, as well as longer-term voter participation in the next statewide election.

For the larger scaled up project we will also collect data for voting in the General Election.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We will randomly divide people in a sample of previously-convicted residents of North Carolina into two groups; the "control" group will not be contacted, while the "treatment" group will be sent a letter telling them about the voter registration process and encouraging them to register if eligible.

For the scaled-up study we will use a between-subjects design with several treatment arms and an (uncontacted) control group.
Experimental Design Details
In North Carolina, people who have been convicted of felonies are eligible to vote after they have completed their sentences (including any probation or parole). North Carolina’s Department of Public Safety (DPS) provides publicly available data containing personal information for everyone who has been in NC DPS custody since 1972. We will use these data to identify people who were convicted of a felony and have completed the terms of their sentence (248,472 records as of early 2019). We will then use the publicly-available North Carolina voter file to identify and remove those who are already registered to vote from the data. The resulting dataset will include individuals who have completed the terms of their sentences and are, therefore, eligible to vote, but who are not registered to vote. These will be the people we seek to contact in our pilot studies.

In our first pilot study, described here, we will draw a random sample of 10,000 people from this dataset of individuals who have completed sentences and are not registered to vote. We will then contact a data vendor (TouchPoints) to attempt to find current mailing addresses based on their names and date of birth; we will retain everyone matched to an address for assignment to treatment/control. Then, before completing treatment assignment, we will remove individuals residing in the 3rd and 9th Congressional districts. We do this because special elections are being held early in September in these districts, and we worry that our mailer could reach people in these districts after the registration deadline for these elections has passed, thus confusing them about their ability to vote in the special election. We will then randomly assign the remaining individuals in the sample (with valid addresses) to treatment or control conditions with equal probability.

Our treatment will consist of a letter describing the eligibility criteria for registering and voting and encouraging people to register and vote, including a blank voter registration form and a postage-paid envelope for returning it to the local elections office. We will send one letter to everyone in the treatment group; we will not contact the control group. After a pre-specified period of time, we will collect our outcome measures. We will observe whether people have registered to vote by collecting another snapshot of the North Carolina voter file and searching for them. We will also plan to collect voter turnout in the next statewide election. For both outcomes, our first analysis will be a simple difference-in-means comparison between the treatment and control groups.

For the scaled up 2020 trial:
We will select states from which to collect data based on their felon disfranchisement policies, accessibility of administrative data, and the availability of potential research partners for future projects. In North Carolina, for example, people who have been convicted of felonies are eligible to vote after they have completed their sentences (including any probation or parole). North Carolina’s Department of Public Safety (DPS) provides publicly available data containing personal information for everyone who has been in NC DPS custody since 1972. We will use these records and similar records from other states to identify people who were convicted of a felony and have completed the terms of their sentence.

We will then use publicly-available voter files to identify and remove those who are already registered to vote from the data. The resulting dataset will include individuals who have completed the terms of their sentences and are, therefore, eligible to vote, but who are not registered to vote. These will be the population--of non-registered previously-sentenced people--we seek to contact in our study.

Randomization Method
randomization done in office by a computer
Randomization Unit
individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
8,621 people for whom we have addresses in the initial sample.

Across all conditions and control groups, we expect a total sample size of about 161,000 individuals in the 2020 trial.
Sample size: planned number of observations
same as clusters (individual randomization)
Sample size (or number of clusters) by treatment arms
people will be randomized with equal probability into treatment/control conditions (so n/2).

People will be randomized with equal probability into treatment/control conditions for the 2020 expansion.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
MIT COUHES
IRB Approval Date
2019-07-19
IRB Approval Number
1907914986

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