Methodology

Methodology

Heterogeneity in Voter List Maintenance Practices: A Study of Florida Counties

Jian Cao California Institute of Technology
,
Seo-young Silvia Kim Author ORCID home | opens in new tab California Institute of Technology
,
R. Michael Alvarez California Institute of Technology
Abstract
How do we ensure the accuracy and integrity of a statewide voter registration database, which often depends on aggregating decentralized, sub-state data with different list maintenance practices? We present Bayesian multivariate multilevel model to account for common patterns in local data while detecting anomalous patterns, using Florida as our example. We use monthly snapshots of state's voter database to estimate countywide change rates for multiple response variables (e.g., changes in voter's partisan affiliation), and then jointly model their changes. We show that there is much heterogeneity in how counties manage voter lists, resulting in very different patterns in additions, deletions, or changes of records. Our method identifies several Florida counties with anomalous rates of changes in the 2016 election.
Content
Thumbnail image of content item
Supplementary material
Thumbnail image of content item
Online Appendices
Online Appendices for Heterogeneity in Voter List Maintenance Practices: A Study of Florida Counties
Comments
Log in using your APSA account or Register to comment
Comments are not moderated before they are posted, but they can be removed by the site moderators if they are found to be in contravention of our Commenting Policy – please read this policy before you post. Comments should be used for scholarly discussion of the content in question. You can find more information about how to use the commenting feature here .
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.