Resources

The resources below are designed to help election officials manage the process of registering voters and creating, updating, and maintaining voter records.

Using Michigan's voter purge database from 2014 to 2018, this analysis finds that more Democratic leaning areas, denser/more urban areas, and areas with more Black residents had higher purge rates. Notably, while these mediation effects were significant, racial composition and median income (i.e. more black and poorer communities) remained a significant factor in voter purge rates.

This Article calls attention to the development and derailment of a novel cross-governmental bureaucracy for voter registration.

This paper examines an unintended consequence of automatic voter registration: effects on party registration. Examining the state of Oregon, a state with back-end AVR, the analysis documents a significant decreases in partisan voter registration rates.

Using data from Orange County, CA, this research finds that a variation of automatic voter registration that targets existing registrants as opposed to eligible nonregistrants—termed automatic reregistration (ARR)—increases turnout by 5.8 percentage points.

In researching how to ensure a statewide voter registration database’s accuracy and integrity, this analysis develops a Bayesian multivariate multilevel model to account for correlated patterns of change over time in multiple response variables, and label statewide anomalies using deviations from model predictions.

Using monthly data from the Colorado Department of Motor Vehicles from 2017 to 2021, the research studies a series of reforms to the voter registration process conducted by the DMV between 2018 and 2020. Prior to the reforms, a large majority of unregistered DMV patrons declined the opportunity to register when conducting a transaction. When voter registration became the clear default option for certain unregistered Colorado DMV patrons in 2020, very few of them subsequently opted out, which resulted in a sudden, large increase in the rate at which DMV patrons registered to vote.

The results in this article suggest that while convenience measures are designed to improve registration and voting rates, they may not result in across-the-board increases that some policymakers and advocates hope for. Nevertheless, there may be some differential impacts of these innovations on registration and turnout, particularly for youth and minority voters.

This research focuses on how the timing of voter file snapshots affects the most commonly cited advantage of voter file data: accurate measures of who votes.

This research uses difference-in-differences estimates that suggest that same day voter registration disproportionately increases turnout among individuals aged 18–24 (an effect between 3.1 and 7.3 percentage points).

In this paper, authors use snapshots of voter registration files (VRF) over time and machine learning models to test the effectiveness of unsupervised anomaly detection methods in detecting VRF modifications. They find that statistical models comparing administrative districts within a short time span and non-negative matrix factorization are most effective for surfacing anomalous events for review.

In this paper, authors match a high-quality, random sample of the U.S. population to multiple lists revealing that at least 11% of the adult citizenry is not on a voter list. An additional 12% is mislisted (i.e., not living at their recorded address).