National Neighborhood Data Archive (NaNDA): Voter Registration, Turnout, and Partisanship by County, United States, 2004-2018 (ICPSR 38506)

Version Date: Aug 31, 2022

Principal Investigator(s):
Megan Chenoweth, University of Michigan. Institute for Social Research; Mao Li, University of Michigan. Institute for Social Research; Iris N. Gomez-Lopez, University of Michigan. Institute for Social Research; Ken Kollman, University of Michigan. Institute for Social Research

Series:

https://doi.org/10.3886/ICPSR38506.v1

Version V1 ()

  • V2 [2024-10-14]
  • V1 [2022-08-31] unpublished

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Additional details may be in the Version History or Data Collection Notes fields of the study metadata.

2022-08-31 ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection:

  • Checked for undocumented or out-of-range codes.

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Summary

This dataset contains counts of voter registration and voter turnout for all counties in the United States for the years 2004-2018. It also contains measures of each county's Democratic and Republican partisanship, including six-year longitudinal partisan indices for 2006-2016.

Citation

Chenoweth, Megan, Li, Mao, Gomez-Lopez, Iris N., and Kollman, Ken. National Neighborhood Data Archive (NaNDA): Voter Registration, Turnout, and Partisanship by County, United States, 2004-2018. Inter-university Consortium for Political and Social Research [distributor], 2022-08-31. https://doi.org/10.3886/ICPSR38506.v1

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Funding

United States Department of Health and Human Services. Administration for Community Living. National Institute on Disability, Independent Living, and Rehabilitation Research (90RTHF0001), United States Department of Health and Human Services. National Institutes of Health. National Institute on Aging (RF1-AG-057540), United States Department of Health and Human Services. National Institutes of Health. National Institute of Nursing Research (U01NR020556), United States Department of Health and Human Services. National Institutes of Health. National Center on Minority Health and Health Disparities (U01NR020556)

Subject Terms

Geographic Coverage

Smallest Geographic Unit

County Federal Information Processing System (FIPS)

Distributor(s)

Inter-university Consortium for Political and Social Research
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Time Period(s)

2004 -- 2018

Date of Collection

2020

Data Collection Notes

  1. The data and document in this study were originally deposited in openICPSR 125781.
  2. For additional information see the National Neighborhood Data Archive (NaNDA).
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Study Purpose

This dataset was created to explore the relationship between voter engagement (as expressed through registration and turnout rates), partisan political leanings, community health, and public policy.

Study Design

Voter Registration and Turnout

To construct measures of voter registration and turnout, researchers calculated three figures for each county in the United States:

  1. Registered voters: the total number of people registered to vote in the county
  2. Ballots cast: the total number of votes cast in the November general election for each year
  3. Voting population: researchers evaluated three possible measures for this component and selected Citizen Voting Age Population (CVAP), which excludes noncitizens

Researchers then calculated three ratios using these components:

  1. Voter registration: registered voters / voting population
  2. Voter turnout: ballots cast / voting population
  3. Registered voter turnout: ballots cast / registered voters

Partisanship

For the years 2006-2016, researchers calculated Democratic and Republican partisanship indices for each county based on its voting history in presidential and senate races over the current and three prior elections. Researchers built this index based on votes for president and senator because these races occur consistently in even years all fifty U.S. states.

Researchers extracted votes for Democratic and Republican presidential candidates from county-level data on presidential election outcomes for the years 2000-2016. For senate races, researchers summarized 2000-2016 precinct-level votes for Democratic and Republican candidates to the county level, then joined them with the presidential election vote counts. This resulted in four figures per county per year:

  1. PRES_DEM_VOTES: Votes for Democratic presidential candidates
  2. PRES_REP_VOTES: Votes for Republican presidential candidates
  3. SEN_DEM_VOTES: Votes for Democratic senate candidates
  4. SEN_REP_VOTES: Votes for Republican senate candidates

For each county and year, researchers created four ratios:

  1. PRES_DEM_RATIO: PRES_DEM_VOTES / (PRES_DEM_VOTES + PRES_REP_VOTES)
  2. PRES_REP_RATIO: PRES_REP_VOTES / (PRES_DEM_VOTES + PRES_REP_VOTES)
  3. SEN_DEM_RATIO: SEN_DEM_VOTES / (SEN_DEM_VOTES + SEN_REP_VOTES)
  4. SEN_REP_RATIO: SEN_REP_VOTES / (SEN_DEM_VOTES + SEN_REP_VOTES)

Researchers then calculated annual Democratic and Republican partisanship indices and six-year aggregate Democratic and Republican partisanship indices for each county for 2006 through 2016. The Democratic index is the average of the presidential and senate Democratic vote ratios over the current and previous four elections. The Republican index is calculated using Republican vote ratios in the same manner. The two indices add up to one for each county and year.

For greater details regarding this process, users should consult the accompanying documentation.

Time Method

Longitudinal

Universe

Counties in the United States, excluding Alaska and island territories.

Unit(s) of Observation

Time Unit

Data Source

The data and document in this study were originally deposited in openICPSR 125781.

Partisanship indices are constructed from county-level presidential election results and precinct-level senate election results. All presidential race data comes from the MIT Election Data and Science Lab (2018a). Senate race data for 2000-2014 comes from the Harvard Election Data Archive (Ansolabehere et al., 2014, Ansolabehere et al., 2018). Senate race data from 2016 come from the MIT Election Data and Science Lab (2018b).

Data on voter registration and turnout was taken from the Election Administration and Voting Survey (EAVS) datasets (United States Election Assistance Commission, 2004-2018). The EAVS is conducted every two years following a federal election by the United States Election Assistance Commission (USEAC). Information on voting, voter registration, and election administration is collected from local election officials at the state and county levels (USEAC, 2020).

Citizen voting age population (CVAP), which is used to calculate voter turnout, was taken from United States Census Bureau data sources, specifically the 2000 decennial census and the 2012 and 2017 American Community Survey five-year estimates. More information about how the researchers selected CVAP for each year is available in the methodology section of this codebook.

Data Type(s)

Mode of Data Collection

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Original Release Date

2022-08-31

Version History

2022-08-31 ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection:

  • Checked for undocumented or out-of-range codes.

Hide