Evidence map›Paper›PMID 40229253›Full record

ArticleScientific data2025

GERDA: The German Election Database.

Vincent Heddesheimer, Hanno Hilbig, Florian Sichart, Andreas Wiedemann

Erratum issuedAbstract read
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Vincent HeddesheimerPrinceton University, Department of Politics, Princeton, NJ, 08544, USA.
Hanno HilbigUniversity of California, Davis, Department of Political Science, Davis, CA, 95616, USA. hhilbig@ucdavis.edu.
Florian SichartPrinceton University, Department of Politics, Princeton, NJ, 08544, USA.ORCID http://orcid.org/0000-0003-2622-489X
Andreas WiedemannPrinceton University, Department of Politics, Princeton, NJ, 08544, USA.ORCID http://orcid.org/0000-0003-1805-7008

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Elections are the key mechanism through which voters hold elected officials accountable. The partisan composition of local, state, and federal governments, in turn, shapes policy choices and public goods provision. Yet studying representation, government responsiveness, and partisan politics across multiple levels of government-especially at the local level-has been difficult due to inconsistently reported, incomplete, or insufficiently harmonized election data at small geographic scales. This paper introduces GERDA ( https://www.german-elections.com/ ), a panel dataset of local, state, and federal election results in Germany at the municipality level spanning the past three decades. GERDA includes turnout and vote shares for all major parties and resolves challenges arising from municipal boundary changes and joint mail-in voting districts, yielding a consistent panel of municipalities in their 2021 boundaries. We also provide municipal and county boundary shapefiles to facilitate spatial analyses. Our dataset enables new research on partisan politics, policy responsiveness, and political representation at fine-grained geographic scales and over time.

Identifiers

PMID40229253
PMCPMC11997170

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.