The governor’s race in Georgia involving the current Secretary of State, Brian Kemp, has highlighted a longstanding concern of many in the election law, election science, and election administration community–electing those public officials who oversee and administer elections. Rick Hasen captures the spirit of these concerns in his quote to Governing magazine:
It is a problem that we have partisan-elected secretaries of state as the chief election officers,” says Rick Hasen, a professor of law and political science at the University of California, Irvine.
Of course, this issue is magnified by having the chief elections officer running for higher office, simultaneous with sometimes important–and politically fraught– decisions that have to be made about eligibility for the registration rolls, times and places for early voting, allocation of election machines and poll workers, even potentially decisions about recounts (this latter issue is what caused a controversy in the Republican primary for Kansas governor involving Secretary of State Kris Kobach).
(Crossposted to electionupdates.caltech.edu)
I look forward to a more detailed analysis by voter registration and database match experts of the GAI report that will be presented to the Presidential Advisory Commission on Election Integrity , but even a cursory reading reveals a number of serious misunderstandings and confusions that call into question that authors’ understanding of some of the most basic facts about voter registration, voting, and elections administration in the United States.
Fair warning: I grade student papers as part of my job, and one of the comments I make most often is “be precise”. Categories and definitions are fundamentally important, especially in a highly politicized environment like that current surrounding American elections.
The GAI report is far from precise; it’s not a stretch to say at many points that it’s sloppy and misinformed. I worry that it’s purposefully misleading. Perhaps I overstate the importance of some of the mistakes below. I leave that for the reader to judge.
- The report uses an overly broad and inaccurate definition of vote fraud.
American voter lists are designed to tolerate invalid voter registration records, which do not equate to invalid votes, because to do otherwise would lead to eligible voters being prevented from casting legal votes.
But the report follows a very common and misleading attempt to conflate errors in the voter rolls with “voter fraud”. Read their “definition”:
Voter fraud is defined as illegal interference with the process of an election. It can take many forms, including voter impersonation, vote buying, noncitizen voting, dead voters, felon voting, fraudulent addresses, registration fraud, elections officials fraud, and duplicate voting.8
Where did this definition come from? As the source of the definition, they cite the Brennan Center report “The Truth About Voter Fraud” (https://www.brennancenter.org/sites/default/files/legacy/The%20Truth%20About%20Voter%20Fraud.pdf).
However, the Brennan Center authors are very careful to define voter fraud. From Pg. 4 of their report in a way that directly warns against an overly broad and imprecise definition:
Voter fraud” is fraud by voters. More precisely, “voter fraud” occurs when individuals cast ballots despite knowing that they are ineligible to vote, in an attempt to defraud the election system.1
This sounds straightforward. And yet, voter fraud is often conflated, intentionally or unintentionally, with other forms of election misconduct or irregularities.
To be fair to the authors, they do not conflate in their analysis situations such as being registered in two places at once with “voter fraud”, but the definition is sloppy, isn’t supported by the report they cite, and reinforces a highly misleading claim that voter registration errors are analogous to voter fraud.
David Becker can describe ad nauseam how damaging this misinterpretation has been.
- The report makes unsubstantiated claims about the efficacy of Voter ID in preventing voter fraud.
Regardless of how you feel about voter ID, if you are going to claim that voter ID prevents in-person vote fraud, you need to provide actual proof, not just a supposition. The report authors write:
GAI also found several irregularities that increase the potential for voter fraud, such as improper voter registration addresses, erroneous voter roll birthdates, and the lack of definitive identification required to vote.
The key term here is “definitive identification”, a term that appears nowhere in HAVAThe authors either purposely or sloppily misstate the legal requirements of HAVA. On pg. 20 of the report, they write that HAVA has a
“requirement that eligible voters use definitive forms of identification when registering to vote”
The word “definitive” appears again, and a bit later in the paragraph, it appears that a “definitive” ID, according to the authors, is:
“Valid drivers’ license numbers and the last four digits of an individual’s social security number…”,
But not according to HAVA. HAVA requirements are, as stated in the report:
“Alternative forms of identification include state ID cards, passports, military IDs, employee IDs, student IDs, bank statements, utility bills, and pay stubs.”
The rhetorical turn occurs at the end of the paragraph, when the authors conclude that these other forms of ID are:
“less reliable than the driver’s license and social security number standard”. This portion of the is far from precise.
and apparently not “definitive” and hence prone to fraud.
Surely the authors don’t intend to imply that a passport is “less reliable” than a drivers license and social security number. In many (most?) states, a “state ID card” is just as reliable as a drivers license. I’m not familiar with the identification requirements for a military ID—perhaps an expert can help out?[ED NOTE: I am informed by a friend that a civilian ID at the Pentagon requires a retinal scan and fingerprints]–but are military IDs really less “definitive” than a driver’s license?
If you are going to claim that voter fraud is an issue requiring immediate national attention, and that states are not requiring “definitive” IDs, you’d better get some of the most basic details of the most basic laws and procedures correct.
- The authors claim states did not comply with their data requests, when it appears that state officials were simply following state law
The authors write:
(t)he Help America Vote Act of 2002 mandates that every state maintains a centralized statewide database of voter registrations.14
That’s fine, but the authors seem to think this means that HAVA requires that the states make this information available to researchers at little to no cost. Anyone who has worked in this field knows that many states have laws that restrict this information to registered political entities. Most states restrict the number of data items that can be released in the interests of confidentiality.
Rather than acknowledging that state officials are constrained by state law, the authors claim non-compliance:
In effect, Massachusetts and other states withhold this data from the public.
I can just hear the gnashing of teeth in the 50 state capitols.I am sympathetic with the authors’ difficulties in obtaining statewide voter registration and voter history files. Along with the authors, I would like to see all state files be available for a low or modest fee, and to researchers.
There is no requirement that the database be made available for an affordable fee, nor that the database be available beyond political entitles. These choices are left to the states. it is wrong to charge “non-compliance” when an official is following statute (passed by their state legislatures).
I don’t know whether the report authors didn’t have subject matter knowledge or were purposefully trying to create a misleading image of non-cooperation with the Commission.
- The report shows that voter fraud is nearly non-existent, while simultaneously
claiming the problem requires “immediate attention”.
But let’s return to the bottom line conclusion of the report: voter fraud is pervasive enough to require “immediate attention.” Do their data support this claim?
The most basic calculation would be the rate of “voter fraud” as defined in the report The 45,000 figure (total potential illegally cast ballots) is highly problematic, based on imputing from suspect calculations in 21 states, then imputed to 29 other states without considering even the most basic rules of statistical calculation.
Nonetheless, even if you accept the calculation, it translates into a “voter fraud” rate of 0.000323741007194 (45,000 / 139 million), or three thousandths of a percent.
This is almost exactly the probability that you will be struck across your whole lifetime (a chance of 1 in 3000 http://news.nationalgeographic.com/news/2004/06/0623_040623_lightningfacts.html)
I’m not the first one to notice this comparison—see pg. 4 of the Brennan Center report cited below. And here I thought I found something new!
There are many, many experts in election sciences and election administration that could have helped the Commission conduct a careful scientific review of the probability of duplicate registration and duplicate voting. This report, written by Lorraine Minnite more than a decade ago lays out precisely the steps that need to be taken to uncover voter fraud and how statewide voter files should be used in this effort. There are many others in the field including those worried about voter fraud and those who are skeptics of voter fraud who have been calling for just such a careful study.
Unfortunately, the Commission instead chose to consult a “consulting firm” with no experience in the field, and which chose to consult database companies who also had no expertise in the field.
I’m sure that other experts will examine in more detail the calculations about duplicate voting. However, at first look, the report fails the smell test. It’s a real stinker.
—
Paul Gronke
Professor, Reed College
Director, Early Voting Information Center
http://earlyvoting.net
The research team at the Elections Research Center at the University of Wisconsin, Madison, have a new paper analyzing the partisan impact of early voting laws, in combination with a set of other election reforms. The abstract is provided below; the piece is gated at the Political Research Quarterly but may be available from the authors.
Abstract
Conventional political wisdom holds that policies that make voting easier will increase turnout and ultimately benefit Democratic candidates. We challenge this assumption, questioning the ability of party strategists to predict which changes to election law will advantage them. Drawing on previous research, we theorize that voting laws affect who votes in diverse ways depending on the specific ways that they reduce the costs of participating. We assemble datasets of county-level vote returns in the 2004, 2008, and 2012 presidential elections and model these outcomes as a function of early voting and registration laws, using both cross-sectional regression and difference-in-difference models. Unlike Election Day registration, and contrary to conventional wisdom, the results show that early voting generally helps Republicans. We conclude with implications for partisan manipulation of election laws.
The piece is a follow up from the team’s widely cited 2014 piece (conveniently available because it is part of the North Carolina case)that shows that early voting may have a mixed effect on turnout, depending on the mix of other election reforms that are already in place.
I like what the authors have done here, and I don’t find it particularly surprising. I’ve never been convinced by the conventional political wisdom that early voting always helps Democrats. That just doesn’t comport with the longstanding findings that Republicans use no-excuse balloting at higher rates than Independents or Democrats. The reasons for this are complex, including what I suspect is a historical legacy of the emergence of direct mail mobilization by Richard Viguerie in the late 1970s, tied to higher rates of absentee voting among older, more conservative, more Republican voters, and Reagan’s roots in California politics.
This kind of suspicion led to some criticism of the 2014 piece because the team coded “early voting” as a single administrative procedure, not discriminating between no-excuse absentee and early in-person. They’ve fixed that here, and the results hold. A key table of results is reproduced below.
I would still caution against overinterpreting these results as providing a roadmap for election law gamesmanship. Burden et al. spend a bit too much time, in my judgment, opining about how partisan actors may or may not misestimate the political impact of reforms to election laws, without acknowledging the highly contingent and dynamic nature of the legal and administrative environment.
For example, it’s almost certain than when a new voting method is made available, strategic political actors from both parties look at these changes, look at what groups opt for one or another method, and start to change their campaigns accordingly. Capturing this kind of institutional dynamic is nearly impossible to do in a national study like this, and can easily make gamesmanship seem a lot simpler than it actually is.
(This is a guest posting from Nick Solomon, Reed College senior in Mathematics)
One of our first assignments in our Election Sciences course was to take a look at the Oregon Motor Voter data and try and tease out any patterns we could find in it.
I’ve always been interested in geographic statistics, so I decided to examine Oregon counties. This can be especially valuable because geography tends to to be a good proxy for making inferences about demographic variables we might not have access to, like income, race, or education level (none of these are accessible via the Oregon statewide voter registration file).
The figure displays party of registration among citizens registered via OMV. It’s important to remember when looking at the graphic that the OMV process initially categorizes all citizens as “NAV” (non-affiliated voters), and citizens must return a postcard designating a party. As of January 2017, as shown on the left, 78% of registrants did not return the card, and only 11% decided to select a party.
The county by county totals are fascinating. OMV voters constitute the highest percentage of registered voters in Malheur county. Many readers may recognize the name–the Malheur National Wildlife Refuge was the site of a 41 day standoff between law enforcement and a small group of occupiers.
Malheur is located in the farthest southeast corner of the state. It’s rural, relatively poor, and much more Republican than the rest of the state. John McCain received 69% of the vote in Malheur in 2008.
In an upcoming blog post, another student will be posting a map of this county by county visualization, and it’s apparent that a number of rural counties have high percentages of OMV registrants.
At the recommendation of a few experts who looked at the graphic I decided to examine the percentage of OMV voters by county versus the total number of registered voters. This lets us get a sense of whether Malheur is an outlier caused by a very small sample size making the percentage value overly sensitive or if this is a number that we can trust.
Here, the total number of voters is plotted on a log scale, as many counties have smaller numbers of voters, while the Portland metro area has many more.
The log scale allows us to get a better sense of any relationship between number of voters and percent registered by OMV without the few large numbers dominating the plot.
This graphic shows that there are quite a few counties of similar size to Malheur, and some that are even smaller. Furthermore, we see that Malheur is not very far from other counties of its size.
Finally, to my eye, there seems to be no meaningful relationship between these two variables, so I find myself concluding that Malheur county, along with Umatilla and Morrow and Curry and Coos are experiencing a much greater benefit in access to voter registration than some larger, more urban counties.
For those interested, these graphics were made with R and ggplot2. I’ll be posting on my personal blog with more details about how I made them.
Eventually, I hope to learn more I was also curious about hoe OMV might be affecting party turnout at the polls. Keep tuned for future updates!
Image courtesy of the National Conference of State Legislatures (http://www.ncsl.org/research/elections-and-campaigns/absentee-and-early-voting.aspx)
A number of Northeast states are considering adding or expanding early voting, according to a story in The Hill.
I hope that administrators and legislators in the states make sure they make a decision based on comprehensive and accurate information and not rely on anecdote.
Most importantly, early voting has a complicated relationship to overall voter turnout. Most studies show a small but positive relationship, though one prominent study reports a negative relationship. If you put in more early voting locations, more citizens vote early (but it’s not clear if more voters overall cast a ballot).
Jan Leighley and Jonathan Nagler put it best in a recent blog posting (in the context of voter registration laws): higher turnout depends mostly on parties and candidates, not on changes to voting laws.
The point? New Hampshire Secretary of State Bill Gardner is quoted in the story and his statement reflects many common misconceptions about early voting:
“We’re seeing turnout nationally go down in each of the last three elections even as more and more states rush to make it easier to vote by having early voting,”
Misconception 1: there has been no “rush” to add early voting options since 2008. The rate of states adding early voting provisions has slowed substantially as we get down the final 13 holdouts (according to the National Conference of State Legislatures, 37 states plus DC offered some form of early voting in 2016, compared to 36 plus DC in 2012, and 34 in 2008).
Misconception 2: turnout has not declined for the last three cycles. Final totals in 2016 appear to be slightly up from 2012 and about 2% lower than 2008.
Misconception 3: national turnout is the best way to understand the impact of state and local laws. National totals disguise enormous variation in turnout between and within states, competitiveness in statewide races, and differences in rules and laws. There is also some scattered evidence that early voting benefits some subpopulations more than others, and this can be overlooked in national and even statewide totals.
The second point in the article is harder to address: the costs of early voting. Michael McDonald suggests that there is resistance to early voting in the Northeast because most of these states administer elections at the township level. McDonald is right to highlight the importance of providing sufficient funding to jurisdictions to conduct elections, regardless of what options are offered (budgets were the most common point of discussion at a recent NCSL gathering).
All I’d add here is that we don’t have a clear sense of how much early voting costs, and whether cost savings can be obtained by strategically reallocating resources between early voting and election day voting (though mis-forecasts of voting turnout can turn disastrous).
The takeaway is that states considering adding early voting options should consider them mostly on the grounds of voter convenience, on how well the options can be adapted to the conditions faced by local jurisdictions, and only lastly on how they may increase overall turnout.
Nate Silver’s posted a quick analysis today that purports to show that “education, not income, predicted who would vote for Trump.” This is a pretty important finding, if true, because it stands in contrast to a lot of post-election analysis that claims that Democratic abandonment of the white working class played a large role in Clinton’s defeat.
It would also be an impressive finding before the major academic surveys, such as the National Election Study and the Cooperative Congressional Election Study are released, since they are the gold standard in terms of helping us understand how individual demographic and attitudes predict vote choice.
Silver takes a smart cut at the income and education relationship by partitioning up counties by their median income and percent college degree, and then comparing the 2016 Clinton vote to the 2012 Obama vote. Here he can show in some of the educated counties, Clinton did remarkably well.
He acknowledges that income and education are highly correlated, however, so he takes a different cut at the data, looking at a set of counties with relatively high educational levels and only moderate income levels.
Silver describes one of these counties, Ingham County, MI, where he grew up, as
…home to Michigan State University and the state capital of Lansing, along with a lot of auto manufacturing jobs (though fewer than there used to be). The university and government jobs attract an educated workforce, but there aren’t a lot of rich people in Ingham County.
Clinton, he notes, did quite well there, even though incomes aren’t that high. In most places that fit this description, according to Silver, Clinton did quite well. This is evidence, he argues, that education, not income, was the driving force in the 2016 election.
This table is r
eproduced here.
Anyone who is familiar with higher education should immediately recognize this list. If you don’t, you will in a moment.
Silver notes that “many of the counties on the list are home to major colleges or universities, although there are some exceptions.” He notes Davidson County, TN and Buncombe County, NC as not “really college towns.”
Not exactly. Below I list the major universities in each of these counties. Silver hit the jackpot with his list: every single one is home to a large university, in most cases, a huge university.
It’s true that college students as a percentage of total residents is pretty small in Davidson, TN and Buncombe, NC, but I’d be pretty skeptical to generalize anything from the homes of country music, bluegrass music–what Silver calls “cultural havens” (Missoula MT and New Hanover NC fit into that category as well).
But the rest? Almost all are college counties. Most are home to huge institutions that are the dominant cultural and economic force in those counties. Of course they have a combination of high education levels and modest income levels. That’s life as a student and employee of a university! It’s no wonder that Clinton did relatively better in those counties.
This list may be indicative of the kind of cultural divide that Silver speculates about at the end of the essay. I’m far less certain that this reveals anything systematic about the relationship of income and education and vote choice more broadly.
I posted on my Reed College introductory politics class “Moodle”. I shared this on Facebook and getting a lot of requests to share more broadly. Any questions about the class readings and other references below, please email paul@earlyvoting.net.
—
Folks,
I’ve spent the day trying to absorb and understand the election results, and I thought it might help to provide a list of resources where I am going to try to reason through this. I certainly don’t mind, and I’m sure Chris would not mind, if people want to talk, or rant, or celebrate, or protest.
We are not suggesting that you should be dispassionate or apolitical about the election outcome. I handle unexpected political changes by doing by best to deconstruct it and understand it. That’s my makeup. It need not be yours. Do what you will with below.
1) The 50,000 Foot Look:
I still think the best place to look and reflect is at a site that allows you to drill down to the county level, and compare vote changes from 2012. I prefer the NY Times, but I list a number of other sites below. Click through at these sites to see the various maps.
The best interactive maps in my opinion at the NY Times: http://www.nytimes.com/elections/results/president
Great mix of maps and exit polls at BBC: http://www.bbc.com/news/election-us-2016-37889032
USA Today does a better job displaying change in support http://www.usatoday.com/…/intera…/how-the-election-unfolded/
CNN has a different look and feel, not my choice but has very nice individual state results http://www.cnn.com/election/results
2) This election is a game changer and this election is a realignment
Most of the evidence is that this election reinforced the existing divisions between the two parties. What was surprising to many observers was that more Republicans did not abandon their party standard bearer, given a lack of endorsements and many leaders distancing themselves from Trump. If you are able to ignore that for a moment, Trump’s support coalition looks nearly identical to Romney’s. Clinton underperformed Obama, especially among African Americans and Latinos. That’s the election in a nutshell.
Larry Bartels at the Monkey Cage examines election 2016 https://www.washingtonpost.com/…/2016-was-an-ordinary-elec…/
3) What about race, ethnicity, gender? Didn’t the horrible things Trump said make a difference?
You know from our class that voters decide based on a wide variety of things–partisanship most importantly, then issues (mostly the economy), and then finally candidate characteristics. It has never been the case that candidate characteristics are the most important consideration. And it is often the case that attitudes about particular “single issues” can overwhelm everything else. While the things Trump said may matter a lot to you, you can’t expect that those same things matter to other people, who may believe in very different things and have very different life experiences. We won’t be able to answer this question in detail for a few months, but I suspect we are going to find not that many Trump voters did not completely ignore the things he said, but they heavily discounted them because of other concerns. And for another big chunk, race and ethnicity in particular get bound up with fear and discontent. That, unfortunately, is very common in the human condition.
This graphic from the NY Times summarizes Trump and Clinton support, compared to elections back to 2004, among key demographics. You may want to look at this first before following up on the links below.http://www.nytimes.com/…/…/elections/exit-poll-analysis.html
3a) On Gender: Clinton simply did not benefit much from her gender, at least that’s what the evidence indicates. Gender identity is very different from racial solidarity, so expecting the gender effect in 2016 to function like the race effect in 2012 and 2008 was probably wishful thinking, no matter how much gender identity may matter to you.
Michael Tesler at the Monkey Cage, with extensive citations to past work on the comparative weakness of gender identity.https://www.washingtonpost.com/…/why-the-gender-gap-doomed…/
3b) On Ethnicity (primarily Latinos): Evidence is far more mixed. The finding you are seeing in the press is that Trump received 29% of the Latino vote, which exceeds Romney’s margin by 9%. However, others are disputing this finding, critiquing the way the exit polls are conducted. This one will be debated for a while.
Matt Barreto of UCLA and Latino Decisions (and older brother of a recent Reed alum in political science) runs down why he thinks the exit polls overestimate Trump support among Latinos http://www.latinodecisions.com/…/the-rundown-on-latino-vot…/ (UPDATE: Nice article at the Monkey Cage.)
3c) On African American support: Clinton did not do as well as Obama among African Americans. If the 88% number holds, that’s down 5% from 2012. But what appears to have been more damaging is lower turnout overall, and this really hurt in states like Florida, Michigan, North Carolina, and Pennsylvania.
Politico story on the number of African Americans in Florida who voted early in 2012 and did not in 2016, citing the work of political scientist Daniel Smith of University of Florida. http://www.politico.com/…/clinton-campaign-struggles-in-get…
Analysis of the exit poll data by political scientists Stanley Feldman and Melissa Herrman http://www.cbsnews.com/…/cbs-news-exit-polls-how-donald-tr…/
4) What about the polls and the forecasts? Does this indicate that polling and statistical forecasting is junk?
It may not surprise that my answer is “no.” There was a systematic miss for the polls, and consequently the forecasts, and the misses were all in red states. If the models were junk, they would have missed in the blue states as well. That means there was something going on in the red states that was missed by the political observers and political scientists who obviously need to scrutinize what they are doing. But your own fundamentals based forecasts predicted Clinton’s vote almost precisely, as did at least two of the forecasts in PS. Something is seriously amiss about Trump support, but there’s no evidence (yet) that there is something seriously amiss about the fundamental underpinnings of election science.
Andrew Gelman does a nice job showing the consistent miss in red states http://andrewgelman.com/…/polls-just-fine-blue-states-blew…/
Gelman shows how a comparatively small yet systematic 2% shift in support toward Trump appears to explain virtually all the “misses.”http://andrewgelman.com/…/11/09/explanations-shocking-2-sh…/
See also Nate Silver http://fivethirtyeight.com/…/what-a-difference-2-percentag…/
Silver reminds us (as you read in his book) that there is a tendency among people to refuse to acknowledge the meaning of uncertainty and probability. He’s to blame as much as anyone for producing these seemingly precise forecasts, but he’s not to blame for reporters and citizens not understanding uncertainty.
http://fivethirtyeight.com/…/final-election-update-theres-…/
While different data sources come up with slightly different estimates, the Current Population Survey’s Voting and Registration Supplement shows that the level of early voting has tripled since 1998 in midterm elections, and has gone up two and half times in presidential years.
If the levels this year are 30% or higher, it will be the most in any midterm. It’s unlikely that this year’s early voting rate will hit the 2016 level of 39%, but it’s possible that we might approach it.