Use our resource library to explore the latest research in the field of election science.
The resources below are designed to help election officials manage the process of registering voters and creating, updating, and maintaining voter records.
This paper provides an empirical analysis of 2020 election audits showing very small changes in presidential vote counts across audited jurisdictions and contest types.
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 paper introduces Bayesian/low-variance risk limiting audit approaches using marginal mark recording to reduce variability and sample requirements.
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.
Academic paper examining the use of audits following elections to improve voter confidence.
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.
In this paper, authors use Orange County, California data to demonstrate efficient audit strategies for many contests and shows how contest selection by discrepancy can reduce workload.
In this paper, authors present ALPHA, a flexible risk limiting audit method that can handle sampling without replacement and stratification while learning from audited ballots.
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).