September 20, 2020

New Study on Effects of E-Voting

David Card and Enrico Moretti, two economists from UC Berkeley, have an interesting new paper that crunches data on the 2004 election, to shed light on the effect of touchscreen voting. The paper looks reasonable to me, but my background is not in social science so others are better placed than me to critique it. Here, I’ll summarize the paper’s findings.

The researchers start with datasets on county-by-county vote results in the 2004 U.S. presidential election, and county-by-county demographics, along with a list of counties that used DREs (i.e., touchscreen voting machines). It turns out that counties that used DREs tended to vote more strongly for Bush than counties that didn’t. This effect, by itself, isn’t very interesting, since there are many possible causes. For example, DREs were more popular in the South, and Bush was more popular there too.

To get a more interesting result, they redid the same calculation, while controlling for many of the factors that might have affected Bush’s vote share. To be specific, they controlled for past voting patterns (Republican and third-party voting shares in the 1992, 1996, and 2000 presidential elections), for county demographics (percent black, percent Hispanic, percent religious, percent college-educated, percent in the military, percent employed in agriculture), for average income, and for county population. They also included a per-state dummy variable that would capture any effects that were the same across all counties in a particular state. After controlling for all of these things, they still found that DRE counties tended to tilt toward Bush, compared to non-DRE counties. This discrepancy, or “DRE effect” amounted to 0.21% of the vote.

So did Republicans steal the election? The researchers turn to that question next. They observe that if the DRE effect was caused by Republican cheating, then we would expect the DRE effect to be larger in places where Republicans had a motive to cheat (because the election was close), and where Republicans had an opportunity to cheat (because they controlled the election bureaucracy). Yet further analysis shows that the DRE effect was not larger in states where the election was close, and was not larger in states with Republican governors or Republicans secretaries of state. Therefore it seems unlikely that outright vote-stealing can account for the DRE effect.

The researchers next looked at how DRE use correlated with voter turnout. They found that voter turnout was roughly 1% lower in counties that used DREs, after controlling for all of the factors listed above. Interestingly, the drop in turnout tended to be larger in counties with larger Hispanic populations. (The same effect does not seem to exist for black voters.) This suggests a possible cause of the DRE effect: DREs may suppress turnout among Hispanic voters, who tend to vote for Democrats overall (although not in Florida).

Why might DREs suppress the Hispanic vote? Perhaps Hispanics are more likely to be intimidated by the high-tech DREs. Perhaps DREs are harder to use for voters who aren’t native English speakers. Perhaps DREs made people wait longer to vote, and Hispanic voters were less able or less willing to wait. Or perhaps there is some other cultural issue that made Hispanic voters wary of DREs.

It’s worth noting, though, that when the researchers estimated the magnitude of the Hispanic-vote-suppression mechanism, they found that it accounted for only about 15% of the overall DRE effect. Most of the DRE effect is still unexplained.

This is an interesting paper, but is far from the last word on the subject.

UPDATE (Thur. May 19): Steve Purpura, who knows this stuff much better than I do, has doubts about this study. See the comments for his take.


  1. They observe that if the DRE effect was caused by Republican cheating, then we would expect the DRE effect to be larger in places where Republicans had a motive to cheat

    Actually, I think this is a very bad assumption. If I were to design a system for rigging elections and getting away with it, I’d be sticking by the KISS system: you pre-rig the machinery to fudge the numbers anywhere that machinery is in use, and you use the same algorithm for every machine, putting a cap on the number of flipped votes so that the numbers aren’t so unreasonable that you can’t spin or bully your way out of the natural questions later. This eliminates reliance on voting officials (who may turn out to be honest even if they’re nominally on your side), and cuts down the number of points of detection.

    It would be interesting to know how many different electronic voting machine manufacturers were involved in this effect, and whether there was a discrepancy in effect strength by manufacturer (i.e. if one particular manufacturer showed significantly less DRE than the rest, you might have identified a company that couldn’t be corrupted).

  2. Cypherpunk says:

    You (or perhaps the authors) are putting a certain spin on this. Even if they had found a positive result, it could equally well be interpreted as that Democrats cheat, but that their cheating is more suited to traditional methods of voting based on paper ballots.

    And in terms of the “wait longer” theory, maybe DREs were faster, so people had to wait longer in the regular lines, and Hispanics were more willing to wait than other groups.

    See? You can spin it both ways, if you try to look at it free of preconceptions.

  3. Cypherpunk,

    Your implication that this is all just spin isn’t right. For example, your theory about line-waiting is flatly contradicted by the data. If your theory were correct, then DRE counties would have higher turnout, and counties with large Hispanic populations would see their turnout increase more. The data show the opposite: DREs depress turnout, and depress it more in counties with large Hispanic populations. So your line-waiting theory is far less plausible than the authors’ theory, if we accept that they crunched the numbers correctly.

    The whole point of studies like this is to reject theories that don’t match the data. If other people come up with plausible theories that match the data equally well, then they deserve consideration too.

  4. Steve Purpura says:

    I’ve only done one quick exercise with their paper, which is to use the precinct level data in a few states (as a substitute for the county data) to test if the effects hold. They did not.

    This is interesting because, in studies examining voting behavior, county level aggregation can misstate effects. One of the better examples of this is in gauging the effects of higher income on tendancy to vote Democratic. While it is true that higher income counties have a greater tendancy to vote Democratic, higher income individuals within the counties are not more likely to vote Democratic. But their incomes shift up the median income for the county and make it appear that higher income is related to voting Democratic.

    The other problem that I have with most of these studies is that they do not control for the variety of election systems used in a county. How many people voted absentee, including permenant absentee? In Florida, how many people voted in the week long run-up (which used different machines) to election day?

  5. Anonymous says:

    The following link to a DU thread should be studied by the authors
    of any report hoping to understand the effect of electronic voting

    Mark Crispin Miller read the report and concluded that e-voting was the perpetrator of the funny numbers from North Carolina.