Simple tests for the extent of vote fraud with absentee and provisional ballots in the 2020 US presidential election

Apr 12, 2022 | Original Research, Vote Fraud

Dr. John Lott’s research on vote fraud can be downloaded and read here. The data and the “do files” for STATA allow people to replicate and check all the results are available in these links.

STATA data files

Do file for all the tables and other regressions.

The data provided here has precinct-level information on absentee, in-person, and provisional ballot voting for counties where alleged fraud occurred during the November 3, 2020 election and in adjacent precincts in counties where no fraud was alleged. County voter turnout is also provided for the ten swing states during the election.

Abstract

This study reports three tests measuring vote fraud in the 2020 US presidential election, although they provide inconsistent evidence. To isolate the impact of a county’s vote-counting process and potential This study reports three tests measuring vote fraud in the 2020 US presidential election, although they provide inconsistent evidence. To isolate the impact of a county’s vote-counting process and potential fraud on candidates’ vote margins, I first compare voting precincts in a county with alleged fraud to adjacent precincts in neighboring counties with no allegations of fraud. I compute the differences in President Trump’s vote shares on absentee ballots in those adjacent precincts, controlling for the differences in his vote shares on ballots cast in person. I also control for registered voters’ demographics and compare data for the 2016 and 2020 presidential elections. When I examine Georgia and Pennsylvania separately, weak evidence of vote fraud on absentee ballots is found. I then apply the same method to provisional ballots in Allegheny County, where, contrary to state law, voters were allowed to correct alleged defects in absentee ballots by submitting provisional ballots on Election Day. My analysis finds that such permission contributed to a statistically significant additional 5,320 to 7,200 votes for Biden. Finally, vote fraud can show up as artificially larger voter turnouts, higher rates of filling out absentee ballots for people who hadn’t voted, dead people voting, ineligible people voting, or payments for votes. The estimates for Arizona, Georgia, Michigan, Nevada, Pennsylvania, and Wisconsin combined indicate between 146,000 and 334,000 excess votes for Biden.

Keywords: Vote fraud, absentee ballots, voter turnout rate, provisional ballots, presidential election

JEL Classification: D72, D73, K16

My responses to Eggers and Grimmer are available Round 1 here but the best place to start might be Round 2 here. The beginning of the summary reads as follows:

Summary Round 1

Addressing Eggers and Grimmer’s claims leaves most of the results largely unchanged. The biggest change is the estimate in Table 9 goes from being negative and statistically significant to being negative and not statistically significant. However, their paper didn’t “replicate” the turnout estimates I provided. Their piece never states that they use a different measure of voter turnout and different control variables. Only by making all these changes can they turn the fraud variable from being consistently positive and statistically significant to being negative and not statistically significant. Simply adopting their measure of voter turnout and using my control variables produces a positive but statistically insignificant result. Since they don’t even mention that they have used a different measure of voter turnout, they never try explaining why their measure is preferable. . . . .

Summary Round 2

My most substantial response involves Eggers and Grimmer’s comments regarding voter turnout rates. Accounting for same-day voter registration, the date of the registration data, or Menominee County does not affect my results. As to their claim that they thought they were just replicating my turnout variable, even if they ignored the variable descriptions titled “voter registration” etc. in the STATA data file that I provided, one would think they would compare simple summary statistics or contact me for any clarification.

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