Resources

In this paper, authors examine the effects of automatic voter registration (AVR) on both registration and turnout. They find that ind it does raise registration rates substantially, that the effect of AVR gradually builds the longer it is in place, and that the different types of AVR have significantly different effects on both registration and turnout.

This book examines the dynamics behind shifts in voter registration rates across the states.

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.

This research finds that when automatic voter registration (AVR) is endorsed by Democratic leaders, Republicans (and independents) expect AVR to reduce the fairness and legitimacy of elections, while Democrats are generally resistant to partisan cues.

In this article, using data from Orange County, California, the researchers develop two methods for evaluating the quality of voter registration data as it changes over time: (a) generating audit data by repeated record linkage across periodic snapshots of a given database and monitoring it for sudden anomalous changes and (b) identifying duplicates via an efficient, automated duplicate detection, and tracking new duplicates and deduplication efforts over time.

This study investigates the reliability of Florida’s voter registration files through a phone survey, asking respondents to verify their records. Authors find 17.7% of registrants fail to verify at least one identifying piece of information.

This research develops and applies a method to estimate how many people voted twice in the 2012 presidential election. It estimates that about one in 4,000 voters cast two ballots, although an audit suggests that the true rate may be lower due to small errors in electronic vote records.

This research argues that local challenges remain when maintaining voters’ registration and voting history information, which undermines the quality of voter lists and the integrity of the electoral process. It analyzes Mississippi’s Statewide Election Management System (SEMS) records and finds that voter registration and voting history errors are linked to the county’s active and inactive registered voter rates and demographic characteristics.

This analysis focuses on whether counties that had previously been “covered” purged voters at a higher rate than noncovered counties after the coverage formula was struck down. It finds increases in purge rate of between 1.5 and 4.5 points in formerly covered jurisdictions post-Shelby, compared with counties that had not been subject to preclearance. Most of the increase came immediately, as the effect in 2014 is substantively and significantly higher than that in 2016.

This study assesses the impact of time and registration source on the rates of rejected voter registration applications by analyzing monthly county-level voter registration reports during the 2012 election cycle in Florida. It finds that there is a dynamic relationship between administrative and seasonal factors at the county level, which condition the rates of rejected voter registrations as the registration deadline approaches.

The results of this study demonstrate that state online voter registration increases voter turnout. The difference-in-difference analysis shows that the states’ implementation of online voter registration increases the turnout of young voters by about 3 percentage points in presidential election years.

The analysis finds notable discrepancies in how voter registration data are reported by localities into Mississippi’s Statewide Election Management System (SEMS), as well as discrepancies in how such data are reported by the state to the EAC’s Election Administration and Voting Survey (EAVS). This suggests that some localities face more challenges in managing records under a hybrid structure than others, which can disproportionately impact voters on Election Day, depending on where they reside.