Full metadata
Title
The Demographics of Polling Places
Description
Elections in the United States are highly decentralized with vast powers given to the states to control laws surrounding voter registration, primary procedures, and polling places even in elections of federal officials. There are many individual factors that predict a person's likelihood of voting including race, education, and age. Historically disenfranchised groups are still disproportionately affected by restrictive voter registration and ID laws which can suppress their turnout. Less understood is how election-day polling place accessibility affects turnout. Absentee and early voting increase accessibility for all voters, but 47 states still rely on election-day polling places. I study how the geographic allocation of polling places and the number of voters assigned to each (polling place load) in Maricopa County, Arizona has affected turnout in primary and general elections between 2006 and 2016 while controlling for the demographics of voting precincts. This represents a significant data problem; voting precincts changed three times during the time studied and polling places themselves can change every election. To aid in analysis, I created a visualization that allows for the exploration of polling place load, precinct demographics, and polling place accessibility metrics in a map view of the county. I find through a spatial regression model that increasing the load on a polling place can decrease the election-day turnout and prohibitively large distances to the polling place have a similar effect. The effect is more pronounced during general elections and is present at varying levels during each of the 12 elections studied. Finally, I discuss how early voting options appear to have little positive effect on overall turnout and may in fact decrease it.
Date Created
2017-12
Contributors
- Hansen, Brett Joseph (Author)
- Maciejewski, Ross (Thesis director)
- Grubesic, Anthony (Committee member)
- Economics Program in CLAS (Contributor)
- School of Mathematical and Statistical Sciences (Contributor)
- Computer Science and Engineering Program (Contributor)
- Barrett, The Honors College (Contributor)
Topical Subject
Resource Type
Extent
26 pages
Language
eng
Copyright Statement
In Copyright
Primary Member of
Series
Academic Year 2017-2018
Handle
https://hdl.handle.net/2286/R.I.45894
Level of coding
minimal
Cataloging Standards
System Created
- 2017-11-22 11:39:52
System Modified
- 2021-08-11 04:09:57
- 3 years 3 months ago
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