Aggregation Level Matters: Evidence from French Electoral Data

L. Russo*, L. Beauguitte

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


This paper, issued from the Cartelec project, raises a methodological issue regarding ecological inference. Studying abstention in two recent French elections in the Parisian agglomeration, a linear regression is launched on three different levels of aggregation: from the finest one (polling station), through cities, to electoral districts (circonscriptions). Tests on multicollinearity clearly indicate that employing the finest level of aggregation allows more variables to be significant, enhances the explanatory power of the model, and improves the collinearity amongst the dependent variables.

Original languageEnglish
Pages (from-to)923-938
Number of pages16
JournalQuality & Quantity
Issue number2
Publication statusPublished - Mar 2014


  • Abstention
  • Ecological inference
  • Linear regression model
  • Multicollinearity
  • Parisian agglomeration
  • Political geography


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