In 2017, Germany saw a significant increase in refugee numbers. To understand how this impacted the federal election, the Research Data Center (FDZ) Ruhr at RWI compiled a unique dataset. Called RWI-GEO-VOTE, it breaks down the election results into tiny 1 km x 1 km grid cells. This detailed dataset covers 175, 758 grid cells and gives insights into how every party fared in terms of valid votes.

How did they manage to gather such localized data? By reassigned votes from polling stations to these grid cells. Absentee ballots were left out of the mix. The dataset creation involved some complex steps, like merging populated grid cells with the smallest German voting units, known as constituencies (Wahlbezirke). Adult population shares were adjusted, and combinations of grid cells were linked to municipalities. Data from election results was added using either electoral district geometries or polling station addresses. For unassigned grid cells, municipal-level data filled the gaps.

This dataset is like a treasure trove for researchers who want to dive deep into election results on a local scale. It's a great tool for anyone trying to understand how local factors can influence national election outcomes.

Election Data Insight: Understanding the 2017 German Vote at a Local Level

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