The Early Voting Information Center
We are a non-partisan academic research center based at Reed College in Portland, Oregon.
Professor Paul Gronke and his team conduct research on early voting and election reform, predominantly in the United States. In addition to our scholarly research, we have worked on projects with the Pew Center on the States, the Federal Election Assistance Commission, the Center for American Progress and a number of state and local elections offices.
The Early Voting Information Center is proud to have co-hosted the inaugural Election Sciences, Reform, and Administration Conference in July of 2017. More information can be found on the conference website.
Professor Gronke's academic credentials--including his curriculum vita, courses taught, and other research papers--can be found at his personal Reed web page.
- Research Analyst: Brian Hamel, PhD student, UCLA Dept. of Political Science.
- Assistant: Laura Swann, Reed College ('19).
- Research Coordinator: Mia Leung, Reed College ('19).
Collapsing the data from individual to date
A hat tip for today’s posting goes to Charles Stewart of MIT, whose “Political Science Laboratory” course inspired me to engage my introductory statistics students in data management using real data sources.
Regular readers of this blog may have seen graphics plotting the daily ballot returns from North Carolina. The graphics are identical to the kind of ballot chasing engaged in by the presidential campaigns, and really any campaign in a state with substantial early voting.
The ballot return information is a public record, and theoretically, any citizen, organization, or campaign should have equal access. Unfortunately, things aren’t so simple. As Michael McDonald reports:
I wish every state made these data available for a free electronic download. If your state does not, I urge you to contact your state legislator and see why not.
But suppose you do have these data: what do you do with them?
It turns out that it’s not very hard to go from individual level vote reports to turnout information, if you have the right toolbox. The tool you need is a statistical program capable of reading in datafiles that have hundreds of thousands of cases. That’s too many for Excel. The most commonly used packages in political science are Stata (the example shown below) and R. (The big advantage of R is that it is publicly available, but I’m not conversant yet with the software. My hopes are that some entrepreneurial reader of this blog will translate the Stata code into R code.)
With the tools in hand, the steps involved can seem confusing, but if you follow the attached presentation, I think not too difficult. In brief:
The file looks something like this
VOTER CODE JOHN SMITH 123 MAIN ST RALEIGH NC … DEM … 10/1/2012 10/15/2012 BY MAIL ACCEPT
DATE DEMS REPS UNA DEMVOTED REPVOTED UNAVOTED
10/15/2012 10,219 9221 8217 123 . .
10/15/2012 10,219 9221 8217 . 347 .
10/15/2012 10,219 9221 8217 . . 456
This made up file shows that on Oct. 15, 123 Democratic ballots were returned, 347 Republican ballots, and 456 Unaffiliated ballots.
Obviously, it’s a bit more complicated than that, but I hope this powerpoint presentation (PDF format) that I prepared for my class can guide anyone through the process. The Stata do file referenced in the Power Point can be downloaded as well.