The paper is by John R. Lott, the economist, and Trump administration official. He did not win a NAS award.there was an excess 70,000-79,000 "Fraudelent votes" across GA, according to NAS award winner economist john lott, which was published in the Social science research network.
The NAS award winner is John W. Lott, a Professor of Mathematics at the University of California, Berkeley.
You've been deceived.
The NAS does not like the economist John Lott all that much, they found his work didn't hold up too well.
In a 1997 article written with David B. Mustard and Lott's subsequent books More Guns, Less Crime and The Bias Against Guns, Lott argued that allowing adults to carry concealed weapons significantly reduces crime in America. In 2004, the National Academy of Sciences (NAS) National Research Council (NRC) conducted a review of current research and data on firearms and violent crime, including Lott's work, and concluded "that with the current evidence it is not possible to determine that there is a causal link between the passage of right-to-carry laws and crime rates." The NAS report wrote of Lott's work, "The initial model specification, when extended to new data, does not show evidence that passage of right-to-carry laws reduces crime. The estimated effects are highly sensitive to seemingly minor changes in the model specification and control variables."
But let's look at the study.
A study like that is not proof of anything. All it can do is point to a change that has happened, but it can't explain the change. A major change that happened in Georgia is that Stacey Adams and many other activists got a lot of voters registered who had been falsely struck off the voter rolls; that would change the outcome of the vote.
You need to prove that the explanation for this must be fraud; and if you can prove the fraud, you don't need the study. It's legally worthless, even if its findings were reasonable. By itself, the study does nothing more than to say "things were different this year"; and that's not evidence of a crime.
He then continues to pick some precincts (we don't know which ones, and he's not using an official source for the precincts), and uses some demographics that I couldn't find the source of in the footnotes (there is no literature section), and does some maths that shows things have changed.
Now, we have a huge difference in absentee voting; we know democrats are more careful about Covid-19 and therefore much more likely to vote absentee; Lott chose to compare Republican Counties to a Democrat county, which potentially explains the difference right there.
And note he doesn't actually show that the precincts are similar demographically, he just says they "should", but he hasn't checked.
So he doesn't really do that; but then how did he pick similar counties? Lott matched precincts so they had a 0.75% average difference in vote share in 2016. If that was his criterium to match precincts, he mathematically ensure he'd see a result even if there was nothing to cause it, because of a well-known effect called "regression to the mean".
Regression to the Mean works like this:
* Take 36 pairs of dice, throw them.
* Look at the differences between the dice. They'll go from 0 to 5, and the average will be 1.9.
* Pick the pairs where the two dice have a difference of 0 or 1 (that should be approximately half of them).
* The chosen dice are your "good" pairs, and the average difference will be ~0.6.
* Now throw just these same dice again.
* The average difference will now be 1.9
Shock! What happened? These were the good dice that had a 0.6 average, and now they're at 1.9!!! Somebody must have messed with them!!!
Obviously there was no manipulation of the dice; but the fact that you picked these dice to begin with was flawed; it made the second throw look significant when really it was just your picking that created this "significance" in the first place.
Unfortunately, we can't easily check whether Lott did that, because he doesn't show his work in that paper. Maybe he had something to hide?
I have to admit I don't understand his tables at all; a correlation coeffcient would usually range from -1 to +1, but his coefficients don't do that. I'm not savvy enough in statistics to have a guess at what he's doing, because, again, this economist hints at what he's doing instead of actually showing his work, which, for all I know, could be riddled with maths errors. Why doesn't Lott show us his data? It's public! Or does he?
tl;dr Lott uses a lot of statistical smoke and mirrors to show "things have changed", but he got to pick what to compare it to, and did not show us how he did the picking. He doesn't have any evidence of fraud. And he didn't get a NAS award, either.