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

06 April 2020, Version 1
This content is an early or alternative research output and has not been peer-reviewed at the time of posting.


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.


voter list maintenance
election administration
2016 election
election integrity

Supplementary materials

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


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