RWI-GEO-VOTE: 2017年德国联邦大选的小规模数据
Melinda Fremerey1, Lukas Hörnig2,3, Sandra Schaffner2
1IW - German Economic Institute, Mailbox 10 19 42, 50459 Köln, Germany.
Data in brief
|November 19, 2024
概括
RWI-GEO-VOTE数据集分析了2017年德国联邦大选的1公里电网单元级. 它探讨了难民流入如何影响政党投票份额,为空间分析提供了细致的见解.
科学领域:
- 政治科学 政治科学是指政治学.
- 地理 地理 地理 地理.
- 经济学 经济学 经济学
背景情况:
- 了解政治偏好的空间分布对于选举分析至关重要.
- 社会人口因素,如难民流入,对投票行为的影响需要细粒度数据.
研究的目的:
- 引入RWI-GEO-VOTE数据集,使2017年德国联邦大选在1公里×1公里电网单元级别的分析成为可能.
- 促进研究难民流入与德国政党投票份额之间的关系.
主要方法:
- 由RWI的鲁尔研究数据中心 (FDZ) 编制的数据,涵盖了175,758个网格单元.
- 从投票站重新分配选票到网格单元,不包括缺席选票.
- 交叉网格单元与选区形状文件,并链接到市政数据以获得选举结果.
主要成果:
- 该数据集提供了2017年德国联邦选举中所有当选政党的细分投票数据.
- 它可以对选举结果进行空间显式分析.
结论:
- 对于研究选举地理和移民对投票模式的影响的研究人员来说,RWI-GEO-VOTE数据集是一个宝贵的资源.
- 它的细粒度性质允许对选举结果的空间动态进行详细的调查.
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