Cited by 100Electoral Systems and Political ParticipationPolitical Conflict and GovernancePolitical Theory and Democracy

Understanding the Adoption of Voter Identification Laws in the American States

Biggers, Daniel R., Hanmer, Michael J.·2017·American Politics Research

Abstract

Recently, many states have reversed the decades-long trend of facilitating ballot access by enacting a wave of laws requesting or requiring identification from registrants before they vote. Identification laws, however, are not an entirely new phenomenon. We offer new theoretical insights regarding how changes in political power influence the adoption of identification laws. In the most extensive analysis to date, we use event history analysis to examine why states adopted a range of identification laws over the past several decades. We consistently find that the propensity to adopt is greatest when control of the governor’s office and legislature switches to Republicans (relationships not previously identified), and that this likelihood increases further as the size of Black and Latino populations in the state expands. We also find that federal legislation in the form of the Help America Vote Act seems to enhance the effects of switches in partisan control.

Integrity signals

Registry

Crossref · 10.1177/1532673x16687266

Cites

0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • As states grow more racially diverse, some voters might demand restrictions on democracy to block the political inclusion and empowerment of new voters of color.

    “As states grow more racially diverse due to immigration and internal migration, 15 some voters might demand restrictions on democracy to block the political inclusion and empowerment of new voters of color (Abrajano and Hajnal 2017; Biggers and Hanmer 2017; Myers and Levy 2018).”

    From Laboratories of Democratic Backsliding (2023) · cites this paper as Biggers and Hanmer 2017

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Biggers, D. R., & Hanmer, M. J.
Affiliations
  • University of California, Riverside (US)
  • University of Maryland, College Park (US)
Corresponding author
Biggers, Daniel R.
Venue
American Politics Research
Published
2017-01-16
Volume
45
Issue
4
Pages
560-588
ISSN
  • 0044-7803 (ISSN-L)
  • 1532-673X
  • 1552-3373
OpenAlex
W2574388879
Cited by
100
References
0
Citations by year
2026: 4 · 2025: 6 · 2024: 19 · 2023: 8 · 2022: 10 · 2021: 12 · 2020: 11 · 2019: 23 · 2018: 6 · 2017: 1
FWCI
54.52
Type
journal article
Language
en
Open access
closed
Locations
American Politics Research (publishedVersion)
Funders
University of Notre Dame
Topics
  • Social Sciences › Political Science and International Relations › Electoral Systems and Political Participation
  • Social Sciences › Sociology and Political Science › Political Conflict and Governance
  • Social Sciences › Political Science and International Relations › Political Theory and Democracy
Keywords
voter ID laws, ballot access, state legislation, partisan control, Republican governors, racial and ethnic minorities, Black voters, Latino voters, Help America Vote Act

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review