Roman Election Indicators for Municipal, National, and European Elections (1993–2023)
by Roberto De Rosa·Updated 2mo ago
187 B1files
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Description
Rome, Italy, provides the geographic scope for this dataset of electoral indicators spanning three decades. The data, created by Roberto De Rosa, includes harmonized time series on turnout, party competition, volatility, and personalization across municipal, national, and European elections from 1993 to 2023. It was last updated in April 2026.
Use Cases
Analyzing long-term trends in voter participation based on turnout and abstention indicators.
Studying party system fragmentation and realignment using the Effective Number of Electoral Parties (ENEP) and Pedersen’s volatility metrics.
Investigating the personal vote in mayoral elections based on the mayor–list gap indicator.
Comparing the timing of electoral changes across different political arenas (municipal, regional, national, European).
Conducting ecological analyses of political culture using behavioral electoral traces.
Strengths
Covers a 30-year time range from 1993 to 2023.
Includes data from four electoral arenas: municipal, regional, national, and European.
Based on official election returns from the Italian Ministry of the Interior (Eligendo).
License is CC-BY-4.0, permitting broad reuse with attribution.
Limitations
Dataset size is 187.0 B, indicating a very limited scope or summary-level data.
Row count and column-level documentation are unknown, complicating suitability assessment.
Description metadata is limited; actual data quality and structure require manual inspection after download.
Provenance
Source
Official election returns from the Italian Ministry of the Interior (Eligendo), complemented by municipio-level series.
Collection Method
Analysis constructs comparable indicators from harmonized time series of election returns.
Time Range
1993–2023
Freshness
Last updated 2026-04-23 05:36:05.
Geography
Rome, Italy
The tiny file size (187.0 B) suggests this may be a summary or indicator file, not a full record-level dataset.