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Registering Re-Entering Citizens to Vote
Last registered on September 02, 2020

Pre-Trial

Trial Information
General Information
Title
Registering Re-Entering Citizens to Vote
RCT ID
AEARCTR-0004574
Initial registration date
August 13, 2019
Last updated
September 02, 2020 1:41 PM EDT
Location(s)

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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. September 02. https://doi.org/10.1257/rct.4574-2.1.
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 use a between-subjects design with five groups: 1) control (uncontacted); 2) contacted with a letter from our partner organization with felony-targeted introductory language, information about eligibility, a registration form and stamped envelope; 3) treatment 2 minus the felony-targeted introductory language; 4) treatment 2 minus the registration form and envelope; 5) treatment 2 plus a stronger encouragement to register that informs recipients of the importance of voting to elect representatives who will shape civil rights and criminal justice policies.

We are also conducting a second trial focusing on individuals who live in the same zip codes as those in our main study, but who administrative records do not indicate have previous felony convictions. We can use the results of this study to compare responses in our population of interest (those with previous convictions) to those in the broader population. This trial will have two arms: 1) control (uncontacted); 2) a letter from a partner or us with information about eligibility, plus a form + stamped envelope. (treatment arm 3 from the main study).
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 scaled up trial, we will collect the following outcome variables after each state’s voter registration deadline and after the 2020 General Election: voter registration and whether an individual casts a ballot in the 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 five arms, one of which will be an (uncontacted) control group. The study will be fielded in North Carolina and Texas. We will randomize at the individual level with equal probability across the five treatment groups, blocking on state, using the "randomize" function from the "experiment" library in R. The comparison (no-record) group is randomized (individually) with equal probability into treatment and control.
Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer.
Randomization Unit
individual

For the scaled-up trial: individual, blocking on state
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 the two trials all conditions and control groups, we expect a total sample size of about 160,703 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, blocking on state, for the 2020 expansion.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
With respect to power, we have performed power calculations aimed at testing the sample size needed to identify differences between treatment arms. We assumed a baseline control-group registration rate of 2%, which was the average registration rate across all three of our pilot studies. We believe that in our main study, the sample size of 125,000 people, with 25,000 in control, should allow us to detect a minimum treatment effect of .28 percentage points. Comparing the control to any one of the treatment arms (each of which included 25,000 people) will allow us to detect a minimum treatment effect of .35 percentage points. These minimal detectable effects are substantially smaller than the effects we saw in our pilot studies. In our second study, with a total of 35,708 individuals equally split between treatment and control, we should be able to detect a minimum treatment effect of .41 percentage points.
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
MIT COUHES
IRB Approval Date
2019-07-19
IRB Approval Number
1907914986