https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3728626
Conclusion
This study has applied Benford’s law to detect irregularities in county-level voting data for the 2020 US Presidential election. The distribution of digits for voting counts is consistently anomalous across all estimations and robustness checks for Democrats in states their candidate has won, including key swing states, and for Republicans in safely blue states. The observed voting patterns are significantly different from first-digit and two-digit Benford’s law, the empirical distribution observed in past elections, and Monte Carlo simulated distributions.
The contribution of this piece of research is two-fold. First, it evidences the applicability of Benford’s law to election analysis and develops a set of novel robustness tests that can be applied in future studies on the topic. Second, it provides some consistent evidence for anomalous behaviour of vote counts in the 2020 US Presidential election, most importantly in key swing states, which potentially warrants further research and academic investigation.
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