Differential Registration Bias in Voter File Data: A Sensitivity Analysis Approach
Abstract
The widespread availability of voter files has improved the study of participation in American politics, but the lack of comprehensive data on nonregistrants creates difficult inferential issues. Most notably, observational studies that examine turnout rates among registrants often implicitly condition on registration, a posttreatment variable that can induce bias if the treatment of interest also affects the likelihood of registration. We introduce a sensitivity analysis to assess the potential bias induced by this problem, which we call differential registration bias. Our approach is most helpful for studies that estimate turnout among registrants using posttreatment registration data, but it is also valuable for studies that estimate turnout among the voting‐eligible population using secondary sources. We illustrate our approach with two studies of voting eligibility effects on subsequent turnout among young voters. In both cases, eligibility appears to decrease turnout, but these effects are found to be highly sensitive to differential registration bias.
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The ATE can be point identified if researchers collected two additional numbers: the count of total minority and white encounters, within levels of covariates X where applicable.
“we show in Online Appendix A.6 that the ATE can be point identi fi ed if researchers collected two additional numbers: the count of total minority and white encounters, within levels of covariates X where applicable”
From Administrative Records Mask Racially Biased Policing (2020) · cites this paper as Nyhan, Skovron, and Titiunik (2017)
Cites
Endogenous Selection Bias: The Problem of Conditioning on a Collider Variable
Elwert, F., & Winship, C. (2014) · Annual Review of Sociology · doi:10.1146/annurev-soc-071913-043455 · Cited by 1,168 · see citing works
Persistence in Political Participation
Meredith, M. (2009) · Quarterly Journal of Political Science · doi:10.1561/100.00009015 · Cited by 210 · see citing works
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Administrative Records Mask Racially Biased Policing
KNOX, D., LOWE, W., & MUMMOLO, J. (2020) · American Political Science Review · doi:10.1017/s0003055420000039 · Cited by 314 · see citing works
- Authors
- Nyhan, B., Skovron, C., & Titiunik, R.
- Affiliations
- Dartmouth College (US)
- University of Michigan (US)
- Venue
- American Journal of Political Science
- Publisher
- Wiley
- Published
- 2017-01-18
- Volume
- 61
- Issue
- 3
- Pages
- 744-760
- ISSN
- 0092-5853 (ISSN-L)
- 1540-5907
- OpenAlex
- W2574693737
- Cited by
- 68
- References
- 2
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 6 · 2023: 8 · 2022: 7 · 2021: 9 · 2020: 22 · 2019: 5 · 2018: 3 · 2017: 2
- FWCI
- 42.55
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- American Journal of Political Science (publishedVersion)
- Funders
- Robert Wood Johnson Foundation
- National Science Foundation (SES 1357561)
- Topics
- Social Sciences › Political Science and International Relations › Electoral Systems and Political Participation
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Keywords
- voter files, voter turnout, sensitivity analysis, voter eligibility, young voters, voter registration
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