Differential Registration Bias in Voter File Data: A Sensitivity Analysis Approach

Brendan Nyhan, Christopher Skovron, Rocío Titiunik

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)744-760
Number of pages17
JournalAmerican Journal of Political Science
Volume61
Issue number3
DOIs
StatePublished - Jul 2017
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Sociology and Political Science
  • Political Science and International Relations

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