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.
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.
I posted this query on the Political Methdology listserv:
Hello all, I have some students in an election sciences class who want to do some visualizations using CCES data. I’d like them to use the survey weights if possible, but don’t know an easy way to do this in R.
I have come across this package that claims to support graphics and complex survey weights, but can’t find a reference or vignette that uses any graphics: http://r-survey.r-forge.r-project.org/survey/
And have provided a review of the answers:
Thanks to Jay Lee of Reed College for helping me assemble this.
Thanks to those participants in the Political Methodology listserv who responded to a query that I posted a month ago about how to produce survey “toplines” using either Stata or R. The attached document provides a detailed summary of the responses; I have posted the most useful reply here.
From: Paul Gronke <firstname.lastname@example.org>
Quick question for the list: Lisa Bryant (CU Fresno) and I are preparing some “top lines” and “tabs” for a client with whom we conducted a survey.
If you have seen these before, they are usually organized so that categorial survey responses are reported on the rows, and the columns report the overall responses, then responses “tabbed” or “crossed” by various demographic and political categories. Roll your eyes if you will that this is just a big set of exploratory cross tabs, but a lot of folks expect to see them to help digest the survey results.
A typical “tab” looks like this:
VARIABLE Total GOP IND DEM MEN WOMEN …
Category 1 N % N % N % N % N % N %
Category 2 N % …
From: Jonathan Mendelson
I posted a response to the list, but it hasn’t gone through yet, so I thought I’d reply directly. I encountered the same issue as you and wrote a Stata package that essentially creates “tabs” in spreadsheet form. You can install it in Stata via “ssc install tabsheet” or view information at https://ideas.repec.org/c/boc/bocode/s458128.html; there are examples in the documentation so you should be able to get started fairly quickly.
The program is not particularly flexible, but it is easy to use, and some colleagues at my survey firm have found it very useful. Although it doesn’t currently output to anything other than tab-delimited file (which can be opened in a spreadsheet), with some clever formatting in Excel, you could print the resulting spreadsheet to PDF for something nicer looking.
If you need something more flexible in Stata, I’d recommend tabout, although that may require more work to set up. If you find out about any R packages that do something similar, I’d be interested in hearing about it.
The complete list of responses, including various R and Stata solutions, is provided in this PDF: polmeth-question-survey-tabs
Paper proposals are being invited for a Summer Conference on Election Science, Reform, and Administration, hosted by Reed College and Portland State University, and co-sponsored by the Early Voting Information Center at Reed College and the Election Data and Science Lab at MIT. The conference will be held in Portland, OR from July 27-28, 2017.
The goals of the conference are, first, to provide a forum for scholars in political science, public administration, law, computer science, statistics, and other fields who are working to develop rigorous empirical approaches to the study of how laws and administrative procedures affect the quality of elections in the United States; and, second, to build scientific capacity by identifying major questions in the field, fostering collaboration, and connecting senior and junior scholars.
The conference is designed to facilitate close attention to the papers presented, including extensive feedback and discussion. Therefore, papers should represent new work, with early drafts of papers encouraged.
We hope that a wide variety of topics will be addressed at the conference. We are particularly interested in new and innovative projects that address long standing questions about the impact of election reforms on registration and turnout at both the state and federal level; how the voter experience has improved or eroded during the two recent waves of election reform; and the research design and methodological challenges in election science. The following is a list provides a few sample ideas, but should not be considered exhaustive:
- How new or changed election laws affect the size and makeup of the pool of registered voters and the federal, state, and/or local electorates;
- Professionalization (or the lack thereof) and the quality of election administration;
- Evaluating the impact of voting centers, consolidated precincts, and convenience voting;
- How election reform has differentially impacted historically disadvantaged segments of the electorate;
- The analytical and methodological tools needed to work with voter registration and voter history files, and challenges in making causal inferences when working with these files;
- New methods for connecting other behavioral records (e.g. survey data) or geospatial data with voter history and voter turnout data
Airfare, lodging, and conference meals will be covered for paper presenters and discussants. Other scholars are welcome to attend if they can cover conference costs (details to be announced within a month).
Lonna Atkeson, University of New Mexico, and Bernard Fraga, Indiana University, will serve as program co-chairs, and Paul Gronke, Reed College and Phil Keisling, Center for Public Service at PSU, will act as conference organizers and hosts.
Paper proposals of no more than 250 words should be submitted by April 15, 2017. Submit proposals at http://bit.ly/PDXelection – we expect to announce decisions by May 1. Any questions can be sent to email@example.com, firstname.lastname@example.org, or email@example.com.
Scholars wishing to attend without presenting a paper should also contact Emily Hebbron (firstname.lastname@example.org) by May 1st. Further details about the conference will posted on the conference Web site soon thereafter.
Please feel free to re-distribute this announcement to relevant individuals and e-mail lists. We look forward to reading your paper proposals!
Lonna Atkeson, Bernard Fraga, and Paul Gronke
From the email:
The Election Law Program (ELP) is a joint project of William & Mary Law School and the National Center for State Courts. ELP develops resources to assist judges in understanding the unique challenges election litigation presents. ELP is seeking a full-time Program Manager to help oversee and execute Program projects.
The Election Law Program Manager will be responsible for implementing a grant to expand ELP tools and resources, including the eBenchbook project. The Program Manager will be responsible for conducting legal research, coordinating with state election law experts and officials, and supervising student research. The Program Manager will also participate in strategic planning processes and oversee implementation of ELP projects.
Bachelor’s degree required; JD strongly preferred
Demonstrated legal research experience; non-profit experience a plus.
Demonstrated strong communication and organizational skills, with excellent attention to detail.
Demonstrated ability to work independently and to manage multiple tasks.
Demonstrated experience in project management.
Previous experience supervising others.
Background in election law/election administration preferred
Strong graphic design, computer and web skills a plus.
More information about this position is available here and here. Please contact Rebecca Green at email@example.com with questions.
Secretary of State Dennis Richardson continues to try to make a mark, this time by creating a task force to study the feasibility of an independent redistricting commission in the state. Richardson has penned an op-ed about the effort published by Pamplin Media.
More information as this process moves forward.
Always love reposting that image!
(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!
Over the next few weeks, I hope to be featuring on this blog postings from students who are in a new course being offered at Reed College: Data Sciences / Election Sciences.
The course is a collaborative effort with Andrew Bray, a statistics professor at Reed College, and is partially supported by a Student Digital Research grant from the Andrew Mellon Foundation (more information about the grant and the projects it has supported at Reed is contained at this website.)
What better question to have these young scientists answer than the impact of Oregon’s innovative automatic registration system, aptly named “Oregon Motor Voter”? We hope to go beyond the reports provided by the Oregon Secretary of State to understand not just who is being registered via OMV, but who votes as a result of the law, and how the electorate has changed, and may change in the future, as a consequence of this reform.
Step one is going to be a set of pretty data visualizations to whet the appetite. Expect more very soon!
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.