John Lott's Paper on Election Fraud

[Mendel]

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.

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3756988

The paper is by John R. Lott, the economist, and Trump administration official. He did not win a NAS award.
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.

Article:

In a 1997 article written with David B. Mustard[10] 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."[11] 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."[12]

Source: https://en.wikipedia.org/wiki/John_Lott

But let's look at the study.

This study provides measures of vote fraud in the 2020 presidential election. It first compares Fulton county’s precincts that are adjacent to similar precincts in neighboring counties that had no allegations of fraud to isolate the impact of Fulton county’s vote-counting process (including potential fraud). In measuring the difference in President Trump’s vote share of the absentee ballots for these adjacent precincts, we account for the difference in his vote share of the in-person voting and the difference in registered voters’ demographics

Content from external source

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.

To examine that, I looked at precinct-level data for Fulton County and the four Republican counties that border it and no fraud has been alleged: Carroll, Cherokee, Coweta, and Forsyth. The idea is a simple one: compare Trump’s share of absentee ballots in precincts adjacent to each other on opposite sides of a county border. The comparison is made between precincts in Fulton and these four other counties as well as between precincts in these four counties where they are adjacent each other. Comparing a county were fraud is alleged to ones without alleged fraud is simpler than comparing counties where there might be hard-to-specify varying degrees of fraud.

Precincts adjacent to each other on opposite sides of a county border should be relatively similar demographically. There are 384 precincts in Fulton County and 42 precincts in Cherokee County in 2020. In one case, Fulton County precinct ML02A matches up with four different precincts in Cherokee County (Mountain Road 28, Avery 3, Union Hill 38 and a small portion of Freehome 18). The goal is to compare the precincts of Fulton county that are most similar to precincts nearby counties that had no allegations of fraud, in order to isolate the impact of Fulton county’s vote-counting process (including potential fraud).

Content from external source

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.

 

[Mendel]

The thing I would have wanted to do with Lott's data is run the same process on those 4 Republican counties; they're adjacent to each other as well, right? So if Lott is right, then he shouldn't see any effects if he does this comparison.

 

[trevor]

The paper is by John R. Lott, the economist, and Trump administration official. He did not win a NAS award.
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.

Article:

In a 1997 article written with David B. Mustard[10] 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."[11] 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."[12]

Source: https://en.wikipedia.org/wiki/John_Lott

But let's look at the study.

This study provides measures of vote fraud in the 2020 presidential election. It first compares Fulton county’s precincts that are adjacent to similar precincts in neighboring counties that had no allegations of fraud to isolate the impact of Fulton county’s vote-counting process (including potential fraud). In measuring the difference in President Trump’s vote share of the absentee ballots for these adjacent precincts, we account for the difference in his vote share of the in-person voting and the difference in registered voters’ demographics

Content from external source

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.

To examine that, I looked at precinct-level data for Fulton County and the four Republican counties that border it and no fraud has been alleged: Carroll, Cherokee, Coweta, and Forsyth. The idea is a simple one: compare Trump’s share of absentee ballots in precincts adjacent to each other on opposite sides of a county border. The comparison is made between precincts in Fulton and these four other counties as well as between precincts in these four counties where they are adjacent each other. Comparing a county were fraud is alleged to ones without alleged fraud is simpler than comparing counties where there might be hard-to-specify varying degrees of fraud.

Precincts adjacent to each other on opposite sides of a county border should be relatively similar demographically. There are 384 precincts in Fulton County and 42 precincts in Cherokee County in 2020. In one case, Fulton County precinct ML02A matches up with four different precincts in Cherokee County (Mountain Road 28, Avery 3, Union Hill 38 and a small portion of Freehome 18). The goal is to compare the precincts of Fulton county that are most similar to precincts nearby counties that had no allegations of fraud, in order to isolate the impact of Fulton county’s vote-counting process (including potential fraud).

Content from external source

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.

Wow i got the wrong john lott, that was sloppy of me.

"
In a 1997 article written with David B. Mustard[10] 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."[11] 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."[12]"

Not sure how that's possible considering women alone on average defend themselves with fire arms from sexual predators between tens of thousands of time yearly, and "According to the Centers for Disease Control and Prevention, almost every major study on defensive gun use has found that Americans use their firearms defensively between 500,000 and 3 million times each year. There’s good reason to believe that most defensive gun uses are never reported to law enforcement, much less picked up by local or national media outlets." I don't know why you would even mention gun data right now, considering you can just glance at the statistics these days and come up with the obvious conclusions yourself. Gun's PREVENT more crimes then they cause,

"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"

Which is why i asked you to look at it, because i sure as hell couldn't do it.

"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 guess you or i can't prove either or.

Good work on that paper though, you did poke a few holes in it.

Anyways, Again.

""You can't legally release the data but you can change all the rules to the election without going through any court of law{paraphrazed}"" there are only 2 answers to that. either you can legally adjust your rules as a county to favor your political bias Which would mean, IT'S RIGGED, (not through fraud, but rigged and pointless) or they did it illegally....which one is it? moderator deleted my comment, probably because there was "something to hide" Said it was somehow off topic even though a similar question was asked during that phone call, which is what this entire thread was about.

 

[Mendel]

I don't know why you would even mention gun data right now

I'm mentioning that because you brought up the NAS as an authority, and the wikipedia article shows the NAS finds flaws with John R. Lott's work. You said the NAS gave him an award, I said the NAS doesn't like his work very much.

I'm not debunking gun control myths for you in this topic, but I suggest you actually read the 2004 NAS review of the evidence, and then criticize that in the appropriate forum.

If you want to talk about Trump's request for Raffensperger to share election data, you should continue the discussion on that in https://www.metabunk.org/threads/trumps-call-with-brad-raffensperger.11524/ .