Aggregation Level Matters: Evidence from French Electoral Data

L. Russo, L. Beauguitte

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

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
Volume48
Issue number2
DOIs
Publication statusPublished - Mar 2014

Keywords

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

Cite this